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19 pages, 5512 KiB

Open AccessArticle

Voltage Signals Measured Directly at the Battery and via On-Board Diagnostics: A Comparison

by Gereon Kortenbruck, Lukas Jakubczyk and Daniel Frank Nowak

Vehicles 2023, 5(2), 637-655; https://doi.org/10.3390/vehicles5020035 - 30 May 2023

Cited by 4 | Viewed by 2505

Abstract

Nowadays, cars are an essential part of daily life, and failures, especially of the engine, need to be avoided. Here, we used the determination of the battery voltage as a reference measurement to determine possible malfunctions. Thereby, we compared the use of a [...] Read more.

Nowadays, cars are an essential part of daily life, and failures, especially of the engine, need to be avoided. Here, we used the determination of the battery voltage as a reference measurement to determine possible malfunctions. Thereby, we compared the use of a digital oscilloscope with the direct measurement of the battery voltage via the electronic control unit. The two devices were evaluated based on criteria such as price, sampling rate, parallel measurements, simplicity, and technical understanding required. Results showed that the oscilloscope (Picoscope 3204D MSO) is more suitable for complex measurements due to its higher sampling rate, accuracy, and versatility. The on-board diagnostics (VCDS HEX-V2) is more accessible to non-professionals, but it is limited in its capabilities. We found that the use of an oscilloscope, specifically the Picoscope, is preferable to measure battery voltage during the engine start-up process, as it provides more accurate and reliable results. However, further investigation is required to analyse numerous influences on the cranking process and the final decision for the appropriate measurement device is case specific. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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20 pages, 5587 KiB

Open AccessArticle

RDE Calibration—Evaluating Fundamentals of Clustering Approaches to Support the Calibration Process

by Sascha Krysmon, Johannes Claßen, Stefan Pischinger, Georgi Trendafilov, Marc Düzgün and Frank Dorscheidt

Vehicles 2023, 5(2), 404-423; https://doi.org/10.3390/vehicles5020023 - 30 Mar 2023

Cited by 3 | Viewed by 2815

Abstract

The topics of climate change and pollutant emission reduction are dominating societal discussions in many areas. In automotive development, with the introduction of real driving emissions (RDE) testing and the upcoming EU7 legislation, there are endless boundary conditions and potential scenarios that need [...] Read more.

The topics of climate change and pollutant emission reduction are dominating societal discussions in many areas. In automotive development, with the introduction of real driving emissions (RDE) testing and the upcoming EU7 legislation, there are endless boundary conditions and potential scenarios that need to be evaluated. In terms of vehicle calibration, this is leading to a strong focus on alternative approaches such as virtual calibration. Due to the flexibility of virtual test environments and the variety of RDE scenarios, the amount of data collected is rapidly increasing. Supporting the calibration engineers in using the available data and identifying relevant information and test scenarios requires efficient approaches to data analysis. This paper therefore discusses the potential of data clustering to support this process. Using a previously developed approach for event detection in emission calibration, a methodology for the automatic categorization of events is presented. Approaches to clustering algorithms (hierarchical, partitioning, and density-based) are discussed and applied to data of interest. Their suitability for different signals is investigated exemplarily, and the relevant inputs are analyzed for their usability in calibration procedures. It is shown which clustering approaches have the potential to be implemented in the vehicle calibration process to provide added value to data evaluation by calibration engineers. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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20 pages, 2904 KiB

Open AccessArticle

Enhancement of Vehicle Eco-Driving Applicability through Road Infrastructure Design and Exploitation

by Alex Coiret, Pierre-Olivier Vandanjon and Romain Noël

Vehicles 2023, 5(1), 367-386; https://doi.org/10.3390/vehicles5010021 - 14 Mar 2023

Cited by 3 | Viewed by 2063

Abstract

Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility [...] Read more.

Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility and the road’s longitudinal profile. First, a criterion is proposed in order to detect speed policies that are impeding drivers’ eco-driving ability. Then, an energy evaluation is carried out and an optimization is proposed. A numerical application is performed on a speed limiting point with 20 usage cases and 5 longitudinal slope values. In the hypothesis of a longitudinal slope of zero, energy savings of 27.7 liter per day could be realized by a speed sign displacement of only 153.6 m. Potential energy savings can increase to up to 308.4 L per day for a

- 4 %

slope case, or up to 70.5 L per day for an ordinary

- 2 %

slope, with a sign displacement of only 391.5 m. This results in a total of 771,975 L of fuel savings over a 30 year infrastructure life cycle period. Therefore a methodology has been developed to help road managers optimize their speed policies with the aim of moderating vehicle consumption. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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25 pages, 14207 KiB

Open AccessArticle

Vehicle Dynamics and Train-Induced Ground Vibration—Theoretical Analyses and Simultaneous Vehicle, Track, and Soil Measurements

by Lutz Auersch

Vehicles 2023, 5(1), 223-247; https://doi.org/10.3390/vehicles5010013 - 8 Feb 2023

Cited by 4 | Viewed by 2297

Abstract

Ground vibrations near railway lines are generated by the forces that are acting between wheel and rail. It seems to be a straight forward assumption that the vehicle dynamics are important for the level and the frequencies of the excitation forces. Different vehicle [...] Read more.

Ground vibrations near railway lines are generated by the forces that are acting between wheel and rail. It seems to be a straight forward assumption that the vehicle dynamics are important for the level and the frequencies of the excitation forces. Different vehicle dynamics phenomena are analysed for their role in the excitation of ground vibrations: rigid body modes of the bogies, elastic (bending) modes of the car body, and elastic modes of the wheelset. The theoretical analyses use rigid body models, simplified elastic models, and detailed elastic models. Some of these problems are vehicle–track interaction problems where 3D finite-element boundary-element models have been used for the track and soil. It is shown that the rigid or flexible vehicle modes are well in the frequency range of ground vibrations (4 to 100 Hz). They have an influence on the excitation force but the additional forces are rather small and can be neglected in ground vibration prediction. The theoretical results are checked by experimental results of a simultaneous measurement of vehicle, track, and ground vibrations. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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23 pages, 6593 KiB

Open AccessArticle

Impact of Rain Intensity on Interstate Traffic Speeds Using Connected Vehicle Data

by Rahul Suryakant Sakhare, Yunchang Zhang, Howell Li and Darcy M. Bullock

Vehicles 2023, 5(1), 133-155; https://doi.org/10.3390/vehicles5010009 - 31 Jan 2023

Cited by 7 | Viewed by 4139

Abstract

With the emergence of connected vehicle data and high-resolution weather data, there is an opportunity to develop models with high spatial-temporal fidelity to characterize the impact of weather on interstate traffic speeds. In this study, 275,422 trip records from 41,234 unique journeys on [...] Read more.

With the emergence of connected vehicle data and high-resolution weather data, there is an opportunity to develop models with high spatial-temporal fidelity to characterize the impact of weather on interstate traffic speeds. In this study, 275,422 trip records from 41,234 unique journeys on 42 rainy days in 2021 and 2022 were obtained. These trip records are categorized as no rain, slight rain, moderate rain, heavy rain, and very heavy rain periods using the precipitation rate from NOAA High-Resolution Rapid-Refresh (HRRR) data. It was observed that average speeds decreased by approximately 8.4% during conditions classified as very heavy rain compared to no rain. Similarly, the interquartile range of traffic speeds increased from 8.34 mph to 12.24 mph as the rain intensity increased. This study also developed a disaggregate approach using logit models to characterize the relationship between weather-related variables (precipitation rate, visibility, temperature, wind, and day or night) and interstate speed reductions. Estimation results reveal that the odds ratio of reducing speed is 5.8% higher for drivers if the precipitation rate is increased by 1 mm/h. The headwind was found to have a positive significant impact of only up to a 10% speed reduction, and speed reduction is greater during nighttime conditions compared to daytime conditions by a factor of 1.68. The additional explanatory variables shed light on drivers’ speed selection in adverse weather environments, providing more information than the single precipitation intensity measure. Results from this study will be particularly helpful for agencies and automobile manufacturers to provide advance warnings to drivers and establish thresholds for autonomous vehicle control. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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19 pages, 7177 KiB

Open AccessArticle

Vehicle Directional Cosine Calculation Method

by Derek Hall and Timothy Sands

Vehicles 2023, 5(1), 114-132; https://doi.org/10.3390/vehicles5010008 - 30 Jan 2023

Viewed by 1949

Abstract

Teaching kinematic rotations is a daunting task for even some of the most advanced mathematical minds. However, changing the paradigm can highly simplify envisioning and explaining the three-dimensional rotations. This paradigm change allows a high school student with an understanding of geometry to [...] Read more.

Teaching kinematic rotations is a daunting task for even some of the most advanced mathematical minds. However, changing the paradigm can highly simplify envisioning and explaining the three-dimensional rotations. This paradigm change allows a high school student with an understanding of geometry to develop the matrix and explain the rotations at a collegiate level. The proposed method includes the assumption of a point (P) within the initial three-dimensional frame with axes (

{\hat{x}}_{i}

,

{\hat{y}}_{i}

,

{\hat{z}}_{i}

). The method then utilizes a two-dimensional rotation view (2DRV) to measure how the coordinates of point P translate after a rotation around the initial axis. The equations are used in matrix notation to develop a rotation matrix for follow-on direction cosine matrixes. The method removes the requirement to use Euler’s formula, ultimately, providing a high school student with an elementary and repeatable process to compose and explain kinematic rotations, which are critical to attitude direction control systems commonly found in vehicles. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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17 pages, 3224 KiB

Open AccessArticle

Nature-Inspired Optimal Route Network Design for Shared Autonomous Vehicles

by Theodoros Alpos, Christina Iliopoulou and Konstantinos Kepaptsoglou

Vehicles 2023, 5(1), 24-40; https://doi.org/10.3390/vehicles5010002 - 24 Dec 2022

Cited by 2 | Viewed by 2357

Abstract

Emerging forms of shared mobility call for new vehicle routing models that take into account vehicle sharing, ride sharing and autonomous vehicle fleets. This study deals with the design of an optimal route network for autonomous vehicles, considering both vehicle sharing and ride [...] Read more.

Emerging forms of shared mobility call for new vehicle routing models that take into account vehicle sharing, ride sharing and autonomous vehicle fleets. This study deals with the design of an optimal route network for autonomous vehicles, considering both vehicle sharing and ride sharing. The problem is modeled as a one-to-many-to-one vehicle routing problem with vehicle capacity and range constraints. An ant colony optimization algorithm is applied to the problem in order to construct a set of routes that satisfies user requests under operational constraints. Results show that the algorithm is able to produce solutions in relatively short computational times, while exploiting the possibility of ride sharing to reduce operating costs. Results also underline the potential of exploiting shared autonomous vehicles in the context of a taxi service for booking trips through electronic reservation systems. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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20 pages, 4520 KiB

Open AccessArticle

From Human to Autonomous Driving: A Method to Identify and Draw Up the Driving Behaviour of Connected Autonomous Vehicles

by Giandomenico Caruso, Mohammad Kia Yousefi and Lorenzo Mussone

Vehicles 2022, 4(4), 1430-1449; https://doi.org/10.3390/vehicles4040075 - 15 Dec 2022

Cited by 4 | Viewed by 2850

Abstract

The driving behaviour of Connected and Automated Vehicles (CAVs) may influence the final acceptance of this technology. Developing a driving style suitable for most people implies the evaluation of alternatives that must be validated. Intelligent Virtual Drivers (IVDs), whose behaviour is controlled by [...] Read more.

The driving behaviour of Connected and Automated Vehicles (CAVs) may influence the final acceptance of this technology. Developing a driving style suitable for most people implies the evaluation of alternatives that must be validated. Intelligent Virtual Drivers (IVDs), whose behaviour is controlled by a program, can test different driving styles along a specific route. However, multiple combinations of IVD settings may lead to similar outcomes due to their high variability. The paper proposes a method to identify the IVD settings that can be used as a reference for a given route. The method is based on the cluster analysis of vehicular data produced by a group of IVDs with different settings driving along a virtual road scenario. Vehicular data are clustered to find IVDs representing a driving style to classify human drivers who previously drove on the same route with a driving simulator. The classification is based on the distances between the different vehicular signals calculated for the IVD and recorded for human drivers. The paper includes a case study showing the practical use of the method applied on an actual road circuit. The case study demonstrated that the proposed method allowed identifying three IVDs, among 29 simulated, which have been subsequently used as a reference to cluster 26 human driving styles. These representative IVDs, which ideally replicate the driving style of human drivers, can be used to support the development of CAVs control logic that better fits human expectations. A closing discussion about the flexibility of the method in terms of the different natures of data collection, allowed for depicting future applications and perspectives. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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22 pages, 994 KiB

Open AccessArticle

Advantage Actor-Critic for Autonomous Intersection Management

by John Ayeelyan, Guan-Hung Lee, Hsiu-Chun Hsu and Pao-Ann Hsiung

Vehicles 2022, 4(4), 1391-1412; https://doi.org/10.3390/vehicles4040073 - 12 Dec 2022

Cited by 4 | Viewed by 2359

Abstract

With increasing urban population, there are more and more vehicles, causing traffic congestion. In order to solve this problem, the development of an efficient and fair intersection management system is an important issue. With the development of intelligent transportation systems, the computing efficiency [...] Read more.

With increasing urban population, there are more and more vehicles, causing traffic congestion. In order to solve this problem, the development of an efficient and fair intersection management system is an important issue. With the development of intelligent transportation systems, the computing efficiency of vehicles and vehicle-to-vehicle communications are becoming more advanced, which can be used to good advantage in developing smarter systems. As such, Autonomous Intersection Management (AIM) proposals have been widely discussed. This research proposes an intersection management system based on Advantage Actor-Critic (A2C) which is a type of reinforcement learning. This method can lead to a fair and efficient intersection resource allocation strategy being learned. In our proposed approach, we design a reward function and then use this reward function to encourage a fair allocation of intersection resources. The proposed approach uses a brake-safe control to ensure that autonomous moving vehicles travel safely. An experiment is performed using the SUMO simulator to simulate traffic at an isolated intersection, and the experimental performance is compared with Fast First Service (FFS) and GAMEOPT in terms of throughput, fairness, and maximum waiting time. The proposed approach increases fairness by 20% to 40%, and the maximum waiting time is reduced by 20% to 36% in high traffic flow. The inflow rates are increased, average waiting time is reduced, and throughput is increased. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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26 pages, 2003 KiB

Open AccessArticle

Machine Learning-Based Control for Fuel Cell Hybrid Buses: From Average Load Power Prediction to Energy Management

by Hujun Peng, Jianxiang Li, Kai Deng and Kay Hameyer

Vehicles 2022, 4(4), 1365-1390; https://doi.org/10.3390/vehicles4040072 - 5 Dec 2022

Cited by 2 | Viewed by 2654

Abstract

In this work, a machine learning-based energy management system is developed using a long short-term memory (LSTM) network for fuel cell hybrid buses. The neural network implicitly learns the complex relationship between various factors and the optimal power control from massive data. The [...] Read more.

In this work, a machine learning-based energy management system is developed using a long short-term memory (LSTM) network for fuel cell hybrid buses. The neural network implicitly learns the complex relationship between various factors and the optimal power control from massive data. The selection of the neural network inputs is inspired by the adaptive Pontryagin’s minimum principle (APMP) strategy. Since an estimated value of the global average fuel cell power is required in the machine learning-based energy management strategy (EMS), some global features of driving cycles are extracted and then applied in a feedforward neural network to predict the average fuel cell power appropriately. The effectiveness of the machine learning-based energy management, with the integration of the mechanism of estimating the average fuel cell power based on the forward neural network, is tested under two different driving cycles from the training environment, with comparisons to a commercially used rule-based strategy. Based on the simulation results, the learning-based strategy outperforms the rule-based strategy regarding the charge-sustaining mode conditions and fuel economy. Moreover, compared to the best offline hydrogen consumption, the machine learning-based strategy consumed 0.58% and 0.36% more than the best offline results for both driving cycles. In contrast, the rule-based strategy consumed 1.80% and 0.96% more than optimal offline results for the two driving cycles, respectively. Finally, simulations under battery and fuel cell aging conditions show that the fuel economy of the machine learning-based strategy experiences no performance degradation under components aging compared to offline strategies. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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26 pages, 5144 KiB

Open AccessArticle

Using Video Analytics to Improve Traffic Intersection Safety and Performance

by Ahan Mishra, Ke Chen, Subhadipto Poddar, Emmanuel Posadas, Anand Rangarajan and Sanjay Ranka

Vehicles 2022, 4(4), 1288-1313; https://doi.org/10.3390/vehicles4040068 - 10 Nov 2022

Cited by 10 | Viewed by 4779

Abstract

Road safety has always been a crucial priority for municipalities, as vehicle accidents claim lives every day. Recent rapid improvements in video collection and processing technologies enable traffic researchers to identify and alleviate potentially dangerous situations. This paper illustrates cutting-edge methods by which [...] Read more.

Road safety has always been a crucial priority for municipalities, as vehicle accidents claim lives every day. Recent rapid improvements in video collection and processing technologies enable traffic researchers to identify and alleviate potentially dangerous situations. This paper illustrates cutting-edge methods by which conflict hotspots can be detected in various situations and conditions. Both pedestrian–vehicle and vehicle–vehicle conflict hotspots can be discovered, and we present an original technique for including more information in the graphs with shapes. Conflict hotspot detection, volume hotspot detection, and intersection-service evaluation allow us to understand the safety and performance issues and test countermeasures comprehensively. The selection of appropriate countermeasures is demonstrated by extensive analysis and discussion of two intersections in Gainesville, Florida, USA. Just as important is the evaluation of the efficacy of countermeasures. This paper advocates for selection from a menu of countermeasures at the municipal level, with safety as the top priority. Performance is also considered, and we present a novel concept of a performance–safety trade-off at intersections. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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11 pages, 2725 KiB

Open AccessArticle

Modeling of the Resonant Inverter for Wireless Power Transfer Systems Using the Novel MVLT Method

by Rupesh Kumar Jha, Abhay Kumar, Satya Prakash, Swati Jaiswal, Manuele Bertoluzzo, Anand Kumar, Bhagawati Prasad Joshi and Mattia Forato

Vehicles 2022, 4(4), 1277-1287; https://doi.org/10.3390/vehicles4040067 - 9 Nov 2022

Cited by 34 | Viewed by 2407

Abstract

Wireless power transfer (WPT) is a power transfer technique widely used in many industrial applications, medical applications, and electric vehicles (EVs). This paper deals with the dynamic modeling of the resonant inverter employed in the WPT systems for EVs. To this end, the [...] Read more.

Wireless power transfer (WPT) is a power transfer technique widely used in many industrial applications, medical applications, and electric vehicles (EVs). This paper deals with the dynamic modeling of the resonant inverter employed in the WPT systems for EVs. To this end, the Generalized State-Space Averaging and the Laplace Phasor Transform techniques have been the flagship methods employed so far. In this paper, the modeling of the resonant inverter is accomplished by using the novel Modulated Variable Laplace Transform (MVLT) method. Firstly, the MVLT technique is discussed in detail, and then it is applied to model a study-case resonant inverter. Finally, a study-case resonant inverter is developed and utilized to validate the theoretical results with MATLAB/Simulink. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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14 pages, 7451 KiB

Open AccessArticle

Geometric Path Plans for Perpendicular/Parallel Reverse Parking in a Narrow Parking Spot with Surrounding Space

by Inhwan Han

Vehicles 2022, 4(4), 1195-1208; https://doi.org/10.3390/vehicles4040063 - 22 Oct 2022

Cited by 6 | Viewed by 7866

Abstract

This study proposes geometric path plans composed of two stages to automatically perform perpendicular and parallel parking with a reverse path in a narrow space. In perpendicular parking, the minimum width of the available parking spot is computed before the start of the [...] Read more.

This study proposes geometric path plans composed of two stages to automatically perform perpendicular and parallel parking with a reverse path in a narrow space. In perpendicular parking, the minimum width of the available parking spot is computed before the start of the parking operation, and the availability of parking and the optimal stage of the path plan are determined by considering the surrounding space together. In a similar concept, even in parallel parking, it is possible to determine whether to park by calculating the minimum length of the available parking spot and the number of repetitions of motion before starting the parking operation. The theoretical results for the parking spot and surrounding space related to the geometric path plans of perpendicular and parallel parking were confirmed through model car tests. Efficient automatic parking will be enabled by selecting and establishing an appropriate path plan along with the availability of parking in consideration of the parking spot and the surrounding space before starting the parking operation. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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18 pages, 1039 KiB

Open AccessArticle

Impact of Technological Changes and Taxi Market Regulation on the Taxi Vehicle Fleets—The Case Study of Slovakia

by Kristián Čulík, Karol Hrudkay, Alica Kalašová, Vladimíra Štefancová and Eva Nedeliaková

Vehicles 2022, 4(4), 1158-1175; https://doi.org/10.3390/vehicles4040061 - 15 Oct 2022

Viewed by 2632

Abstract

This paper aims to analyze the recent development of taxi services in Slovakia on two levels. The first is the area of technological change, which includes the use of digital platforms for the closing of the contract between the passenger and the taxi [...] Read more.

This paper aims to analyze the recent development of taxi services in Slovakia on two levels. The first is the area of technological change, which includes the use of digital platforms for the closing of the contract between the passenger and the taxi operator. The second level of perspective is the legislative change. Commonly used taxi digital platforms (applications) have started to require a taxi concession from self-employed drivers, and many other requirements. We will also analyze the issue of value-added tax. This article processes quantitative data on the number of valid taxi concessions. The data were obtained from the unified information system in road transport and supplemented with other statistical inputs. The article describes the distribution of more than 6819 issued concessions in individual regions and analyzes 12,477 taxi vehicles registered in these licenses for operating a taxi service. This article also includes the numbers of performed technical and emission inspections of taxi vehicles. With these data, it is possible to prove a sharp increase in interest in the concession due to the introduction of digital applications. A significant change in business conditions in this area can lead to an increase in the number of businesses by 70% in larger cities, while the issue of sustainability is questionable. In the last part, the article also deals with the issue of electromobility, and environmental aspects connected with taxi legislation changes. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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13 pages, 1592 KiB

Open AccessArticle

Autonomous Vehicle Control Comparison

by Pruthvi Banginwar and Timothy Sands

Vehicles 2022, 4(4), 1109-1121; https://doi.org/10.3390/vehicles4040059 - 10 Oct 2022

Cited by 6 | Viewed by 2656

Abstract

Self-driving features rely upon autonomous control of vehicle kinetics, and this manuscript compares several disparate approaches to control predominant kinetics. Classical control using feedback of state position and velocities, open-loop optimal control, real-time optimal control, double-integrator patching filters with and without gain-tuning, and [...] Read more.

Self-driving features rely upon autonomous control of vehicle kinetics, and this manuscript compares several disparate approaches to control predominant kinetics. Classical control using feedback of state position and velocities, open-loop optimal control, real-time optimal control, double-integrator patching filters with and without gain-tuning, and control law inversion patching filters accompanying velocity control are assessed in Simulink, and their performances are compared. Optimal controls are found via Pontryagin’s method of optimization utilizing three necessary conditions: Hamiltonian minimization, adjoint equations, and terminal transversality of the endpoint Lagrangian. It is found that real-time optimal control and control-law patching filter with velocity control incorporating optimization are the two best methods overall as judged in Monte Carlo analysis by means and standard deviations of position and rate errors and cost. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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16 pages, 306 KiB

Open AccessArticle

Injury Criteria for Vehicle Safety Assessment: A Review with a Focus Using Human Body Models

by Filippo Germanetti, Dario Fiumarella, Giovanni Belingardi and Alessandro Scattina

Vehicles 2022, 4(4), 1080-1095; https://doi.org/10.3390/vehicles4040057 - 7 Oct 2022

Cited by 8 | Viewed by 3482

Abstract

This paper aims at providing an overview of the most used injury criteria (IC) and injury metrics for the study of the passive safety of vehicles. In particular, the work is focused on the injury criteria that can be adopted when finite element [...] Read more.

This paper aims at providing an overview of the most used injury criteria (IC) and injury metrics for the study of the passive safety of vehicles. In particular, the work is focused on the injury criteria that can be adopted when finite element simulations and Human Body Models (HBMs) are used. The HBMs will result in a fundamental instrument for studying the occupant’s safety in Autonomous Vehicles (AVs) since they allow the analysis of a larger variety of configurations compared to the limitations related to the traditional experimental dummies. In this work, the most relevant IC are reported and classified based on the body segments. In particular, the head, the torso, the spine, the internal organs, and the lower limbs are here considered. The applicability of the injury metrics to the analyses carried out with the HBMs is also discussed. The paper offers a global overview of the injury assessment useful to choose the injury criteria for the study of vehicle passive safety. To this aim, tables of the presented criteria are also reported to provide the available metrics for the considered body damage. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

30 pages, 28633 KiB

Open AccessArticle

Developing, Analyzing, and Evaluating Vehicular Lane Keeping Algorithms Using Electric Vehicles

by Shika Rao, Alexander Quezada, Seth Rodriguez, Cebastian Chinolla, Chan-Jin Chung and Joshua Siegel

Vehicles 2022, 4(4), 1012-1041; https://doi.org/10.3390/vehicles4040055 - 4 Oct 2022

Cited by 2 | Viewed by 3360

Abstract

Robust lane-following algorithms are one of the main challenges in developing effective automated vehicles. In this work, a team of four undergraduate students designed and evaluated several automated lane-following algorithms using computer vision as part of a Research Experience for Undergraduates program funded [...] Read more.

Robust lane-following algorithms are one of the main challenges in developing effective automated vehicles. In this work, a team of four undergraduate students designed and evaluated several automated lane-following algorithms using computer vision as part of a Research Experience for Undergraduates program funded by the National Science Foundation. The developed algorithms use the Robot Operating System (ROS) and the OpenCV library in Python to detect lanes and implement the lane-following logic on the road. The algorithms were tested on a real-world test course using a street-legal vehicle with a high-definition camera as input and a drive-by-wire system for output. Driving data were recorded to compare the performance of human driving to that of the self-driving algorithms on the basis of three criteria: lap completion time, lane positioning infractions, and speed limit infractions. The evaluation of the data showed that the human drivers successfully completed every lap with zero infractions at a 100% success rate in varied weather conditions, whereas, our most reliable algorithms had a success rate of at least 70% with some lane positioning infractions and at lower speeds. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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15 pages, 11467 KiB

Open AccessArticle

Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution

by Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette, Pruthwiraj Santhosh, Troy Kraemer and Bonnie Henderson

Vehicles 2022, 4(4), 942-956; https://doi.org/10.3390/vehicles4040051 - 22 Sep 2022

Cited by 2 | Viewed by 2438

Abstract

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles [...] Read more.

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles is, however, still lagging behind. While conventional exact and non-exact optimal control techniques such as Dynamic Programming and Model Predictive Control have been demonstrated, they suffer from the curse of dimensionality and quickly display limitations with high system complexity and highly stochastic environment operation. This paper demonstrates that Neuroevolution associated drive cycle classification algorithms can infer optimal control strategies for any system complexity and environment, hence streamlining and speeding up the control development process. Neuroevolution also circumvents the integration of low fidelity online plant models, further avoiding prohibitive embedded computing requirements and fidelity loss. This brings the prospect of optimal control to complex multi-physics system applications. The methodology presented here covers the development of the drive cycles used to train and validate the neurocontrollers and classifiers, as well as the application of the Neuroevolution process. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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25 pages, 6549 KiB

Open AccessArticle

Suitability Assessment of NO_x Emissions Measurements with PTI Equipment

by Eugenio Fernández, Abel Ortego, Alicia Valero and Juan J. Alba

Vehicles 2022, 4(4), 917-941; https://doi.org/10.3390/vehicles4040050 - 21 Sep 2022

Cited by 4 | Viewed by 2707

Abstract

The measurement of NO_x emissions in vehicles has so far been exclusively carried out during the type-approval process. For this purpose, high-precision gas measurement laboratory equipment and Portable Emission Measurement Systems (PEMS) are used. Both types of equipment are costly in terms [...] Read more.

The measurement of NO_x emissions in vehicles has so far been exclusively carried out during the type-approval process. For this purpose, high-precision gas measurement laboratory equipment and Portable Emission Measurement Systems (PEMS) are used. Both types of equipment are costly in terms of price, maintenance, complexity, and time of use (calibration and maintenance requirements). Currently, NO_x emissions measurements in Periodic Technical Inspections (PTIs) are being considered, but PEMS or laboratory equipment is unsuitable for this function, and PTI-grade equipment has to be used. Although CO and O₂ are currently being reliably measured with this equipment, there is not enough information about its accuracy for NO_x measurements. Accordingly, in this paper, simultaneous measures have been performed over the same engine in a test cell, with a laboratory and a PTI gas analyser to assess the accuracy of the latter. When performing the test with the most similar conditions found in PTI, our results show that the PTI gas analyser shows an average deviation of 2.6 ppm and 9% rel. with respect to high-precision laboratory equipment for concentrations below 700 ppm NO_x, which can be considered acceptable for periodic technical inspections. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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14 pages, 4617 KiB

Open AccessArticle

Market Review and Technical Properties of Electric Vehicles in Germany

by Christopher Hecht, Kai Gerd Spreuer, Jan Figgener and Dirk Uwe Sauer

Vehicles 2022, 4(4), 903-916; https://doi.org/10.3390/vehicles4040049 - 20 Sep 2022

Cited by 12 | Viewed by 6849

Abstract

Electromobility has grown rapidly, and especially in China, Europe, and the United States. Within Europe, Germany is the largest market. Our goal in this paper is to provide a data-driven overview of the key data, including the number of vehicles sold, place of [...] Read more.

Electromobility has grown rapidly, and especially in China, Europe, and the United States. Within Europe, Germany is the largest market. Our goal in this paper is to provide a data-driven overview of the key data, including the number of vehicles sold, place of registration, battery capacity, and charging power, in Germany. The results were generated by linking car-registration data with the technical details for each car model. We identified more than 84% of the battery electric vehicles in the fleet, but the uncertainty is larger for plug-in hybrid electric vehicles. The number of sold electric vehicles doubled annually over the last two years. Simultaneously, the battery capacity and charging power per vehicle are rising. Combined, the two effects cause the cumulative battery capacity and charging power of the fleet to grow at an even faster pace. The battery energy built into electric vehicles in Germany registered on 1 August 2022 was 50.5 GWh, of which 9.5 GWh belonged to plug-in hybrids. The combined charging system became the dominant charger type for fast charging in Germany, and only 2% of the vehicle fleet used the competing CHAdeMO standard. To allow fellow researchers to work with the data, we published them free of charge on our data platform mobility charts, and we update the data monthly. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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14 pages, 398 KiB

Open AccessArticle

Severity Analysis of Large-Truck Wrong-Way Driving Crashes in the State of Florida

by Salwa Anam, Ghazaleh Azimi, Alireza Rahimi and Xia Jin

Vehicles 2022, 4(3), 766-779; https://doi.org/10.3390/vehicles4030043 - 30 Jul 2022

Cited by 2 | Viewed by 2295

Abstract

Wrong-way driving (WWD) crashes lead to severe injuries and fatalities, especially when a large truck is involved. This study investigates the factors associated with crash-injury severity in large-truck WWD crashes in Florida. Various driver, roadway, weather, and traffic characteristics were explored as explanatory [...] Read more.

Wrong-way driving (WWD) crashes lead to severe injuries and fatalities, especially when a large truck is involved. This study investigates the factors associated with crash-injury severity in large-truck WWD crashes in Florida. Various driver, roadway, weather, and traffic characteristics were explored as explanatory variables through a random parameter ordered logit model. The study also accounted for heterogeneity by identifying random parameters in the model and introducing interaction effects as potential sources of such heterogeneity. The findings indicate that not using a seatbelt, driving under the influence of drugs, and a driving speed of 50–74 mph were more likely to result in fatal crashes. On the contrary, female drivers, private roadways, and sideswipe collisions showed negative impacts on crash-injury severity. The model identified two random parameters, including a speed of 25–49 mph and early-morning crashes. The interaction effects showed that when driving at a speed of 25–49 mph, young drivers (under 20 years old) and middle-aged drivers (36–50 years old) were the sources of heterogeneity, decreasing crash-injury severity. Understanding the contributing factors of large-truck WWD crashes can help policymakers develop safety countermeasures to reduce the associated injury severity and improve truck safety. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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30 pages, 12536 KiB

Open AccessArticle

Precise Evaluation of Repetitive Transient Overvoltages in Motor Windings in Wide-Bandgap Drive Systems

by Ashkan Barzkar and Mona Ghassemi

Vehicles 2022, 4(3), 697-726; https://doi.org/10.3390/vehicles4030040 - 19 Jul 2022

Cited by 2 | Viewed by 2937

Abstract

The increasing interest in employing wide-bandgap (WBG) drive systems has brought about very high power, high-frequency inverters enjoying switching frequencies up to hundreds of kilohertz. However, voltage surges with steep fronts, caused by turning semiconductor switches on/off in inverters, travel through the cable [...] Read more.

The increasing interest in employing wide-bandgap (WBG) drive systems has brought about very high power, high-frequency inverters enjoying switching frequencies up to hundreds of kilohertz. However, voltage surges with steep fronts, caused by turning semiconductor switches on/off in inverters, travel through the cable and are reflected at interfaces due to impedance mismatches, giving rise to overvoltages at motor terminals and in motor windings. The phenomena typically associated with these repetitive overvoltages are partial discharges and heating in the insulation system, both of which contribute to insulation system degradation and may lead to premature failures. In this article, taking the mentioned challenges into account, the repetitive transient overvoltage phenomenon in WBG drive systems is evaluated at motor terminals and in motor windings by implementing a precise multiconductor transmission line (MCTL) model in the time domain considering skin and proximity effects. In this regard, first, a finite element method (FEM) analysis is conducted in COMSOL Multiphysics to calculate parasitic elements of the motor; next, the vector fitting approach is employed to properly account for the frequency dependency of calculated elements, and, finally, the model is developed in EMTP-RV to assess the transient overvoltages at motor terminals and in motor windings. As shown, the harshest situation occurs in turns closer to motor terminals and/or turns closer to the neutral point depending on whether the neutral point is grounded or floating, how different phases are connected, and how motor phases are excited by pulse width modulation (PWM) voltages. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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18 pages, 4596 KiB

Open AccessArticle

Energy Management Strategy in 12-Volt Electrical System Based on Deep Reinforcement Learning

by Ömer Tan, Daniel Jerouschek, Ralph Kennel and Ahmet Taskiran

Vehicles 2022, 4(2), 621-638; https://doi.org/10.3390/vehicles4020036 - 20 Jun 2022

Cited by 1 | Viewed by 2536

Abstract

The increasing electrification in motor vehicles in recent decades can be attributed to higher comfort and safety demands. Strong steering and braking maneuvers reduce the vehicle’s electrical system voltage, which causes the vehicle electrical system voltage to drop below a critical voltage level. [...] Read more.

The increasing electrification in motor vehicles in recent decades can be attributed to higher comfort and safety demands. Strong steering and braking maneuvers reduce the vehicle’s electrical system voltage, which causes the vehicle electrical system voltage to drop below a critical voltage level. A sophisticated electrical energy management system (EEMS) is needed to coordinate the power flows within a 12-volt electrical system. To prevent the voltage supply from being insufficient for safety-critical consumers in such a case, the power consumption of several comfort consumers can be reduced or switched off completely. Rule-based (RB) energy management strategies are often used for this purpose, as they are easy to implement. However, this approach is subject to the limitation that it is vehicle-model-specific. For this reason, deep reinforcement learning (DRL) is used in the present work, which can intervene in a 12-volt electrical system, regardless of the type of vehicle, to ensure safety functions. A simulation-based study with a comprehensive model of a vehicle electric power system is conducted to show that the DRL-based strategy satisfies the main requirements of an actual vehicle. This method is tested in a simulation environment during driving scenarios that are critical for the system’s voltage stability. Finally, this is compared with the rule-based energy management system using actual vehicle measurements. Concluding measurements reveal that this method is able to increase the voltage at the most critical position of the 12-volt electrical system by approximately 0.6 V. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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13 pages, 4062 KiB

Open AccessArticle

CFD Analysis of the Location of a Rear Wing on an Aston Martin DB7 in Order to Optimize Aerodynamics for Motorsports

by Thomas P. O’Driscoll and Andrew R. Barron

Vehicles 2022, 4(2), 608-620; https://doi.org/10.3390/vehicles4020035 - 13 Jun 2022

Viewed by 6500

Abstract

The purpose of this study is to identify the initial lateral and vertical location and angle of attack of a GT4-style rear wing on the rear downforce for an Aston Martin DB7 Vantage, prior to installation. The tests were completed with a two-dimensional [...] Read more.

The purpose of this study is to identify the initial lateral and vertical location and angle of attack of a GT4-style rear wing on the rear downforce for an Aston Martin DB7 Vantage, prior to installation. The tests were completed with a two-dimensional model, using the Computational Fluid Dynamics (CFD) software, Fluent Ansys. The tests were completed using a range of velocities: 60–80 mph. Optimization of the position of the rear wing aerodynamic device was permitted under the Motorsport UK rules for multiple race series. The results show that while the drag decreases the farther back the wing is located, the desired configuration for the rear wing with regard to downforce is when it is positioned ca. 1850 mm back from the center point of the car, with an attack angle of 5°. Unusually, this is to the front of the boot/rear deck, but it is remarkably similar to where Aston Martin set the rear wing on their Le Mans car in 1995, above where the rear windscreen met the boot hinge, which was based upon wind tunnel studies using a scale model. Our results suggest that while 2D simulations of these types cannot give absolute values for downforce due to aerodynamic device location, they can provide low costs, fast simulation time, and a route for a wide range of cars, making the approach accessible to club motorsports, unlike complex 3D simulation and wind tunnel experimentation. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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22 pages, 8353 KiB

Open AccessArticle

Smart Design: Application of an Automatic New Methodology for the Energy Assessment and Redesign of Hybrid Electric Vehicle Mechanical Components

by Umberto Previti, Antonio Galvagno, Giacomo Risitano and Fabio Alberti

Vehicles 2022, 4(2), 586-607; https://doi.org/10.3390/vehicles4020034 - 12 Jun 2022

Cited by 6 | Viewed by 2785

Abstract

This work aimed to develop an automatic new methodology based on establishing if a mechanical component, designed for a conventional propulsion system, is also suitable for hybrid electric propulsion. Change in propulsion system leads to different power delivery and vehicle dynamics, which will [...] Read more.

This work aimed to develop an automatic new methodology based on establishing if a mechanical component, designed for a conventional propulsion system, is also suitable for hybrid electric propulsion. Change in propulsion system leads to different power delivery and vehicle dynamics, which will be reflected in different load conditions acting on the mechanical components. It has been shown that a workflow based on numerical simulations and experimental tests represents a valid approach for the evaluation of the cumulative fatigue damage of a mechanical component. In this work, the front half-shaft of a road car was analyzed. Starting from the acquisition of a speed profile and the definition of a reference vehicle, in terms of geometry and transmission, a numerical model, based on longitudinal vehicle dynamics, was developed for both conventional and hybrid electric transmission. After the validation of the model, the cumulative fatigue damage of the front half-shaft was evaluated. The new design methodology is agile and light; it has been dubbed “Smart Design”. The results show that changing propulsion led to greater fatigue damage, reducing the fatigue life component by 90%. Hence, it is necessary to redesign the mechanical component to make it also suitable for hybrid electric propulsion. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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18 pages, 547 KiB

Open AccessArticle

Optimal Control of Electrified Powertrains in Offline and Online Application Concerning Dimensioning of Li-Ion Batteries

by Felix Deufel, Martin Gießler and Frank Gauterin

Vehicles 2022, 4(2), 464-481; https://doi.org/10.3390/vehicles4020028 - 19 May 2022

Cited by 1 | Viewed by 2250

Abstract

Various energy management systems (driving strategies) have been developed to improve the efficiency of electrified vehicle drives. These include strategies from the field of offline optimization to determine the theoretical optimum for a given system, as well as online strategies designed for an [...] Read more.

Various energy management systems (driving strategies) have been developed to improve the efficiency of electrified vehicle drives. These include strategies from the field of offline optimization to determine the theoretical optimum for a given system, as well as online strategies designed for an on-board application in the vehicle. In this paper, investigations are performed on an SUV electrified by a 48 V hybrid system in P14 topology regarding both offline and online strategies. To calculate the global optimum, the performance of Dynamic Programming (DP) compared to an Equivalent Consumption Minimization Strategy (ECMS) with an iteratively determined equivalence factor is shown. Furthermore, with regard to online energy management strategies (EMS), it is presented how a predictive Online ECMS achieves additional fuel savings compared to a robust, non-predictive implementation. The simulation-based vehicle development allows detailed investigations regarding interactions between battery requirements and EMS. In this context, it is shown how various battery capacities are exploited by the discussed EMS. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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12 pages, 385 KiB

Open AccessArticle

Perceptions of Transport Automation amongst Small- and Medium-Sized Road Haulage Companies in Finland

by Markus Pöllänen, Heikki Liimatainen, Erika Kallionpää, Roni Utriainen, Hanne Tiikkaja, Timo Liljamo, Riku Viri and Steve O'Hern

Vehicles 2022, 4(2), 433-444; https://doi.org/10.3390/vehicles4020026 - 5 May 2022

Cited by 1 | Viewed by 2782

Abstract

Transport automation is increasingly being studied from different perspectives; however, the perceptions of road haulage companies have received less attention. This study explores the views of representatives of small- and medium-sized road haulage companies on transport automation in Finland. We conducted an online [...] Read more.

Transport automation is increasingly being studied from different perspectives; however, the perceptions of road haulage companies have received less attention. This study explores the views of representatives of small- and medium-sized road haulage companies on transport automation in Finland. We conducted an online survey to gather perceptions of automation, which received 254 responses from representatives of a range of different transport industries. The respondents’ views towards automation were generally negative. The overall view was that automation may not be possible for heavy vehicles in Finland due to the adverse weather and driving conditions. The perception was that road haulage automation is unlikely to occur before 2050 in Finland. The results provide valuable insight for vehicle manufacturers, technology developers, policy makers, and haulage companies. As the road haulage industry is dominated by small- and medium-sized companies, hauliers should be supported in actively implementing new technologies. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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22 pages, 13006 KiB

Open AccessArticle

Shared Automated Electric Vehicle Prospects for Low Carbon Road Transportation in British Columbia, Canada

by Orhan Atabay, Ned Djilali and Curran Crawford

Vehicles 2022, 4(1), 102-123; https://doi.org/10.3390/vehicles4010007 - 3 Feb 2022

Cited by 2 | Viewed by 3703

Abstract

This study explores the long-term energy use implications of electrification, automation and sharing of road vehicles in British Columbia, Canada. Energy use is first analyzed for the years 1990–2016 for forward forecasting, and hypothetical scenarios ranging from conservative to disruptive, incorporating various effects [...] Read more.

This study explores the long-term energy use implications of electrification, automation and sharing of road vehicles in British Columbia, Canada. Energy use is first analyzed for the years 1990–2016 for forward forecasting, and hypothetical scenarios ranging from conservative to disruptive, incorporating various effects of road vehicle electrification, sharing and automation, as well as influences of other technology disruptions, such as online shopping and e-learning are presented and used to project the road transportation energy use in B.C. to 2060. Transportation energy use projections are compared to those of the Canadian Energy Regulator (CER). When considering only the effect of vehicle electrification, the scenarios show higher energy savings compared to CER’s scenarios. The combined impact of vehicle electrification and automation leads to decreased energy use to 2060 for all scenarios considered. The energy savings for all scenarios, except for the conservative one, are higher than CER’s projections. When the effects of vehicle electrification, automation and sharing are merged, all scenarios yield energy savings beyond the CER projections. Inclusion of other technology disruptions and the effects of pandemics like COVID-19 reduce transportation demand and provide further energy savings. The BAU scenario given in this study shows energy use decreases compared to 2016 of 26.3%, 49%, 62.24%, 72.1% for the years 2030, 2040, 2050, and 2060 respectively. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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14 pages, 1050 KiB

Open AccessArticle

Battery Electric Vehicle Efficiency Test for Various Velocities

by Anja Konzept, Benedikt Reick, André Kaufmann, Ralf Hermanutz and Ralf Stetter

Vehicles 2022, 4(1), 60-73; https://doi.org/10.3390/vehicles4010004 - 17 Jan 2022

Cited by 7 | Viewed by 4679

Abstract

Since battery electric vehicle (BEV) sales are increasing, the calculation of necessary electric power supply, and energy consumption data, and vehicle range is important. The Worldwide harmonized Light vehicles Test Procedure (WLTP) currently in use can deliver data to collect comparable energy consumption [...] Read more.

Since battery electric vehicle (BEV) sales are increasing, the calculation of necessary electric power supply, and energy consumption data, and vehicle range is important. The Worldwide harmonized Light vehicles Test Procedure (WLTP) currently in use can deliver data to collect comparable energy consumption data for different vehicles on defined chassis dynamometer test cycles. Nevertheless, the energy consumption and so the range of BEVs are also dependent on the individual trajectory of the user. Therefore, five velocity profiles are developed in this work. The maximum speeds are based on typical velocities in German city traffic and extra-urban traffic. The energy required to finish a single velocity profile is assumed to be constant despite varying maximum velocities. With this kind of driving profiles it is possible to create an individual and more precise statement on the energy consumption and the range of a BEV. In this work, the profiles are driven on a chassis dynamometer with an VW e-Up. The vehicle charging efficiency is tested with two different AC charging modes and is also taken into account. The drive efficiencies of the tested vehicle are presented in dependence of the velocity profile driven. Finally the results are compared with a real-driving velocity profile and the energy consumption data obtained by the board computer of the vehicle. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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Review

Jump to: Research, Other

38 pages, 3470 KiB

Open AccessReview

Impact of Transportation Electrification on the Electricity Grid—A Review

by Reza Bayani, Arash F. Soofi, Muhammad Waseem and Saeed D. Manshadi

Vehicles 2022, 4(4), 1042-1079; https://doi.org/10.3390/vehicles4040056 - 6 Oct 2022

Cited by 22 | Viewed by 7123

Abstract

Transportation electrification is a pivotal factor in accelerating the transition to sustainable energy. Electric vehicles (EVs) can operate either as loads or distributed power resources in vehicle-to-grid (V2G) or vehicle-to-vehicle (V2V) linkage. This paper reviews the status quo and the implications of transportation [...] Read more.

Transportation electrification is a pivotal factor in accelerating the transition to sustainable energy. Electric vehicles (EVs) can operate either as loads or distributed power resources in vehicle-to-grid (V2G) or vehicle-to-vehicle (V2V) linkage. This paper reviews the status quo and the implications of transportation electrification in regard to environmental benefits, consumer side impacts, battery technologies, sustainability of batteries, technology trends, utility side impacts, self-driving technologies, and socio-economic benefits. These are crucial subject matters that have not received appropriate research focus in the relevant literature and this review paper aims to explore them. Our findings suggest that transitioning toward cleaner sources of electricity generation should be considered along with transportation electrification. In addition, the lower cost of EV ownership is correlated with higher EV adoption and increased social justice. It is also found that EVs suffer from a higher mile-per-hour charging rate than conventional vehicles, which is an open technological challenge. Literature indicates that electric vehicle penetration will not affect the power grid in short term but charging management is required for higher vehicle penetration in the long-term scenario. The bi-directional power flow in a V2G linkage enhances the efficiency, security, reliability, scalability, and sustainability of the electricity grid. Vehicle-to-Vehicle (V2V) charging/discharging has also been found to be effective to offload the distribution system in presence of high EV loads. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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Other

Jump to: Research, Review

12 pages, 1534 KiB

Open AccessPerspective

Perspectives on Securing the Transportation System

by Raj Bridgelall

Vehicles 2022, 4(4), 1332-1343; https://doi.org/10.3390/vehicles4040070 - 25 Nov 2022

Viewed by 2541

Abstract

The vast, open, and interconnected characteristics of the transportation system make it a prime target for terrorists and hackers. However, there are no standard measures of transport system vulnerability to physical or cyberattacks. The separation of governance over different modes of transport increases [...] Read more.

The vast, open, and interconnected characteristics of the transportation system make it a prime target for terrorists and hackers. However, there are no standard measures of transport system vulnerability to physical or cyberattacks. The separation of governance over different modes of transport increases the difficulty of coordination in developing and enforcing a common security index. This paper contributes a perspective and roadmap toward developing multimodal security indices that can leverage a variety of existing and emerging connected vehicle, sensing, and computing technologies. The proposed technologies include positive train control (PTC), vehicle-to-everything (V2X), weight-in-motion (WIM), advanced air mobility (AAM), remote sensing, and machine learning with cloud intelligence. Full article

(This article belongs to the Special Issue Feature Papers in Vehicles)

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