Special Issue "Intelligent Transportation Systems for Electric Vehicles"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electric Vehicles".

Deadline for manuscript submissions: closed (30 April 2020).

Special Issue Editor

Prof. Dr. Joao Ferreira
Website
Guest Editor

Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions for a Special Issue of Energies on the subject area of “Intelligent Transportation Systems (ITS) for Electric Vehicles (EV)." The EV and Charging Station (CS) markets have been growing exponentially, and a forecast from the International Energy Agency estimates an increase of EV sales from the current 3 million to 125 million by 2030. This raises additional challenges in terms of the network required to fulfill the charging requirements of the EV. The CS market is growing by 40% a year and is currently worth $300 billion. Electromobility and ITS are essential components in decarbonizing road transportation and play an essential role in the mobility process of Smart Cities. ITS also play an essential task in this transformation, owing to the flexibility of the EV charging process and the EV operation, which operates as an energy storage device; it also helps to facilitate the market penetration of renewable energy resources. In parallel, IoT approaches allow the collection of large volumes of data and big data approaches, creating opportunities to develop solutions to overcome challenges such as the ones that emerge from the EV charging process, CS locations, and the reservation of charging spots.

This Special Issue will focus on emerging ITS for EV and applications for electromobility and Smart Grids. Topics of interest for publication include, but are not limited to, the following:

  • Electric Vehicles and Intelligent Transportation Systems
  • Infrastructure studies and solutions for the charging process (CS location, process, and others)
  • Technological developments for EV operation in Smart Grids
  • V2* (Vehicle to Anything) process and connection
  • Intelligent Transportation Systems for EVs
  • Energy supply, storage systems, charging station and process
  • Smart Grids, renewable energy, demand-response
  • Smart Mobility and Cities
  • ITS and big data
  • IoT for ITS and EV
  • Case studies and the assessment of ITS applications and the EV charging process
  • The standardization process

Keywords

  • electromobility
  • intelligent transportation system
  • storage and charging station systems
  • V2*—vehicle to anything or anything to vehicle
  • smart cities and grids
  • IoT and big data

Published Papers (15 papers)

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Research

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Open AccessArticle
A Study on Electric Vehicles Participating in the Load Regulation of Urban Complexes
Energies 2020, 13(11), 2939; https://doi.org/10.3390/en13112939 - 08 Jun 2020
Abstract
Urban complex (UC) is the main place of citizens’ life and work. The construction of an UC often needs to expand the capacity of the power equipment. This paper proposes to use electric vehicles (EVs) in an UC to reduce the power load [...] Read more.
Urban complex (UC) is the main place of citizens’ life and work. The construction of an UC often needs to expand the capacity of the power equipment. This paper proposes to use electric vehicles (EVs) in an UC to reduce the power load of the UC during peak periods, so that lower capacity power equipment can be used to reduce the construction costs of the UC and the transformation of electrical facilities. In order to find the relationship between parking and power load in the UC, the UC is decomposed into different functional areas for research. Then, we build a parking information database for clustering and calculation. Divide the load peak into adjustment intervals of equal duration. The EVs parked in the UC for each regulation interval (RI) are grouped according to parking characteristics. Establish an objective function with the minimum load variance during peak hours. The discharge capacity of each group in each RI is obtained and distributed to each EV to realize peak load reduction of UC. Finally, the results of case analysis show that the strategy can reduce the peak load effectively thus save the cost of UC construction. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Deployment of a Bidirectional MW-Level Electric-Vehicle Extreme Fast Charging Station Enabled by High-Voltage SiC and Intelligent Control
Energies 2020, 13(7), 1840; https://doi.org/10.3390/en13071840 - 10 Apr 2020
Abstract
Considering the fact that electric vehicle battery charging based on the current charging station is time-consuming, the charging technology needs to improve in order to increase charging speed, which could reduce range anxiety and benefit the user experience of electric vehicle (EV). For [...] Read more.
Considering the fact that electric vehicle battery charging based on the current charging station is time-consuming, the charging technology needs to improve in order to increase charging speed, which could reduce range anxiety and benefit the user experience of electric vehicle (EV). For this reason, a 1 MW battery charging station is presented in this paper to eliminate the drawbacks of utilizing the normal 480 VAC as the system input to supply the 1 MW power, such as the low power density caused by the large volume of the 60 Hz transformer and the low efficiency caused by the high current. The proposed system utilizes the grid input of single-phase 8 kVAC and is capable of charging two electric vehicles with 500 kW each, at the same time. Therefore, this paper details how high-voltage SiC power modules are the key enabler technology, as well as the selection of a resonant-type input-series, output-parallel circuitry candidate to secure high power density and efficiency, while intelligently dealing with the transient processes, e.g., pre-charging process and power balancing among modules, and considering the impact on the grid, are both of importance. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Optimal Design for a Shared Swap Charging System Considering the Electric Vehicle Battery Charging Rate
Energies 2020, 13(5), 1213; https://doi.org/10.3390/en13051213 - 06 Mar 2020
Abstract
Swap charging (SC) technology offers the possibility of swapping the batteries of electric vehicles (EVs), providing a perfect solution for achieving a long-distance freeway trip. Based on SC technology, a shared SC system (SSCS) concept is proposed to overcome the difficulties in optimal [...] Read more.
Swap charging (SC) technology offers the possibility of swapping the batteries of electric vehicles (EVs), providing a perfect solution for achieving a long-distance freeway trip. Based on SC technology, a shared SC system (SSCS) concept is proposed to overcome the difficulties in optimal swap battery strategies for a large number of EVs with charging requests and to consider the variance in the battery charging rate simultaneously. To realize the optimal SSCS design, a binary integer programming model is developed to balance the tradeoff between the detour travel cost and the total battery recharge cost in the SSCS. The proposed method is verified with a numerical example of the freeway system in Guangdong Province, China, and can obtain an exact solution using off-the-shelf commercial solvers (e.g., Gurobi). Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
New Dispatching Paradigm in Power Systems Including EV Charging Stations and Dispersed Generation: A Real Test Case
Energies 2020, 13(4), 944; https://doi.org/10.3390/en13040944 - 20 Feb 2020
Abstract
Electric Vehicles (EVs) are becoming one of the main answers to the decarbonization of the transport sector and Renewable Energy Sources (RES) to the decarbonization of the electricity production sector. Nevertheless, their impact on the electric grids cannot be neglected. New paradigms for [...] Read more.
Electric Vehicles (EVs) are becoming one of the main answers to the decarbonization of the transport sector and Renewable Energy Sources (RES) to the decarbonization of the electricity production sector. Nevertheless, their impact on the electric grids cannot be neglected. New paradigms for the management of the grids where they are connected, which are typically distribution grids in Medium Voltage (MV) and Low Voltage (LV), are necessary. A reform of dispatching rules, including the management of distribution grids and the resources there connected, is in progress in Europe. In this paper, a new paradigm linked to the design of reform is proposed and then tested, in reference to a real distribution grid, operated by the main Italian Distribution System Operator (DSO), e-distribuzione. First, in reference to suitable future scenarios of spread of RES-based power plants and EVs charging stations (EVCS), using Power Flow (PF) models, a check of the operation of the distribution grid, in reference to the usual rules of management, is made. Second, a new dispatching model, involving DSO and the resources connected to its grids, is tested, using an Optimal Power Flow (OPF) algorithm. Results show that the new paradigm of dispatching can effectively be useful for preventing some operation problems of the distribution grids. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
A Method for the Optimization of Daily Activity Chains Including Electric Vehicles
Energies 2020, 13(4), 906; https://doi.org/10.3390/en13040906 - 18 Feb 2020
Cited by 3
Abstract
The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework [...] Read more.
The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework to calculate a suitable schedule of activities, taking into account the locations of activities, modes of transport, and the time of attendance to each activity. The priorities of the travelers concerning the spatial and temporal flexibility were considered, as well as the constraints that are related to the limited range of the EVs, the availability of Charging Stations (CS), and the elevation of the road network. In order to model real travel behavior, two charging scenarios were realized. In the first case, the traveler stays in the EV at the CS, and in the second case, the traveler leaves the EV to charge at the CS while conducting another activity at a nearby location. Through a series of tests on synthetic activity chain data, we proved the suitability of the method elaborated for addressing the needs of travelers and being utilized as an optimization method for a modern Intelligent Transportation System (ITS). Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Multi-Objective Shark Smell Optimization Algorithm Using Incorporated Composite Angle Cosine for Automatic Train Operation
Energies 2020, 13(3), 714; https://doi.org/10.3390/en13030714 - 06 Feb 2020
Abstract
In this paper, an improved multi-objective shark smell optimization algorithm using composite angle cosine is proposed for automatic train operation (ATO). Specifically, when solving the problem that the automatic train operation velocity trajectory optimization easily falls into local optimum, the shark smell optimization [...] Read more.
In this paper, an improved multi-objective shark smell optimization algorithm using composite angle cosine is proposed for automatic train operation (ATO). Specifically, when solving the problem that the automatic train operation velocity trajectory optimization easily falls into local optimum, the shark smell optimization algorithm with strong searching ability is adopted, and composite angle cosine is incorporated. In addition, the dual-population evolution mechanism is adopted to restrain the aggregation phenomenon in shark population at the end of the iteration to suppress the local convergence. Correspondingly, the composite angle cosine, considering the numerical difference and preference difference, is used as the evaluation index, which ameliorates the shortcoming that the traditional evaluation index is not objective and reasonable. Finally, the Matlab/simulation and hardware-in-the-loop simulation (HILS) results for automatic train operation show that the improved optimization algorithm proposed in this paper has better optimization performance. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Direct and Indirect Environmental Aspects of an Electric Bus Fleet Under Service
Energies 2020, 13(2), 336; https://doi.org/10.3390/en13020336 - 10 Jan 2020
Abstract
The reduction of pollutant emissions in the field of transportation can be achieved by developing and implementing electric propulsion technologies across a wider range of transportation types. This solution is seen as the only one that can offer, in areas of urban agglomeration, [...] Read more.
The reduction of pollutant emissions in the field of transportation can be achieved by developing and implementing electric propulsion technologies across a wider range of transportation types. This solution is seen as the only one that can offer, in areas of urban agglomeration, a reduction of the emissions caused by the urban transport to zero, as well as an increase in the degree of the health of the citizens. This paper presents an analysis of the direct and indirect environmental aspects of a fleet of real electric buses under service in the city of Cluj-Napoca, Romania. The solution of using 41 electric buses to replace Euro-3 diesel buses (with high pollution levels) in the city’s transport system eliminates a local amount of 668.45 tons of CO2 and 6.41 tons of NOx—pollutant emissions directly associated with harmful effects on human health—annually. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Developing an On-Road Object Detection System Using Monovision and Radar Fusion
Energies 2020, 13(1), 116; https://doi.org/10.3390/en13010116 - 25 Dec 2019
Abstract
In this study, a millimeter-wave (MMW) radar and an onboard camera are used to develop a sensor fusion algorithm for a forward collision warning system. This study proposed integrating an MMW radar and camera to compensate for the deficiencies caused by relying on [...] Read more.
In this study, a millimeter-wave (MMW) radar and an onboard camera are used to develop a sensor fusion algorithm for a forward collision warning system. This study proposed integrating an MMW radar and camera to compensate for the deficiencies caused by relying on a single sensor and to improve frontal object detection rates. Density-based spatial clustering of applications with noise and particle filter algorithms are used in the radar-based object detection system to remove non-object noise and track the target object. Meanwhile, the two-stage vision recognition system can detect and recognize the objects in front of a vehicle. The detected objects include pedestrians, motorcycles, and cars. The spatial alignment uses a radial basis function neural network to learn the conversion relationship between the distance information of the MMW radar and the coordinate information in the image. Then a neural network is utilized for object matching. The sensor with a higher confidence index is selected as the system output. Finally, three kinds of scenario conditions (daytime, nighttime, and rainy-day) were designed to test the performance of the proposed method. The detection rates and the false alarm rates of proposed system were approximately 90.5% and 0.6%, respectively. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
IoT and Blockchain Paradigms for EV Charging System
Energies 2019, 12(15), 2987; https://doi.org/10.3390/en12152987 - 02 Aug 2019
Abstract
In this research work, we apply the Internet of Things (IoT) paradigm with a decentralized blockchain approach to handle the electric vehicle (EV) charging process in shared spaces, such as condominiums. A mobile app handles the user authentication mechanism to initiate the EV [...] Read more.
In this research work, we apply the Internet of Things (IoT) paradigm with a decentralized blockchain approach to handle the electric vehicle (EV) charging process in shared spaces, such as condominiums. A mobile app handles the user authentication mechanism to initiate the EV charging process, where a set of sensors are used for measuring energy consumption, and based on a microcontroller, establish data communication with the mobile app. A blockchain handles financial transitions, and this approach can be replicated to other EV charging scenarios, such as public charging systems in a city, where the mobile device provides an authentication mechanism. A user interface was developed to visualize transactions, gather users’ preferences, and handle power charging limitations due to the usage of a shared infrastructure. The developed approach was tested in a shared space with three EVs using a charging infrastructure for a period of 3.5 months. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Electric Vehicle Charging Process and Parking Guidance App
Energies 2019, 12(11), 2123; https://doi.org/10.3390/en12112123 - 03 Jun 2019
Abstract
This research work presents an information system to handle the problem of real-time guidance towards free charging slot in a city using past date and prediction and collaborative algorithms since there is no real-time system available to provide information if a charging spot [...] Read more.
This research work presents an information system to handle the problem of real-time guidance towards free charging slot in a city using past date and prediction and collaborative algorithms since there is no real-time system available to provide information if a charging spot is free or occupied. We explore the prediction approach using past data correlated with weather conditions. This approach will help the driver in the daily use of his electric vehicle, minimizing the problem of range anxiety, provide guidance towards charging spots with a probability value of being available for charging in a context for the app and smart cities. This work handles the uncertainty of the drivers to get a suitable and vacant place at a charging station because missing real-time information from the system and also during the driving process towards the free charging spot can be taken. We introduce a framework to allow collaboration and prediction process using past related data. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Electric Vehicles’ User Charging Behaviour Simulator for a Smart City
Energies 2019, 12(8), 1470; https://doi.org/10.3390/en12081470 - 18 Apr 2019
Cited by 8
Abstract
The increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread [...] Read more.
The increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread use of electric vehicles is seen as a resource that includes both distributed storage capabilities and the potential for consumption (charging) flexibility. However, to take advantage of the full potential of electric vehicles’ flexibility, it is essential that proper incentives are provided and that the management is performed with the variation of generation. This paper presents a research study on the impact of the variation of the electricity prices on the behavior of electric vehicle’s users. This study compared the benefits when using the variable and fixed charging prices. The variable prices are determined based on the calculation of distribution locational marginal pricing, which are recalculated and adapted continuously accordingly to the users’ trips and behavior. A travel simulation tool was developed for simulating real environments taking into account the behavior of real users. Results show that variable-rate of electricity prices demonstrate to be more advantageous to the users, enabling them to reduce charging costs while contributing to the required flexibility for the system. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Optimal Charging Navigation Strategy Design for Rapid Charging Electric Vehicles
Energies 2019, 12(6), 962; https://doi.org/10.3390/en12060962 - 13 Mar 2019
Cited by 4
Abstract
Electric vehicles (EVs) have become an efficient solution to making a transportation system environmentally friendly. However, as the number of EVs grows, the power demand from charging vehicles increases greatly. An unordered charging strategy for huge EVs affects the stability of a local [...] Read more.
Electric vehicles (EVs) have become an efficient solution to making a transportation system environmentally friendly. However, as the number of EVs grows, the power demand from charging vehicles increases greatly. An unordered charging strategy for huge EVs affects the stability of a local power grid, especially during peak times. It becomes serious under the rapid charging mode, in which the EVs will be charged fully within a shorter time. In contrast to regular charging, the power quality (e.g.,voltages deviation, harmonic distortion) is affected when multiple EVs perform rapid charging at the same station simultaneously. To reduce the impacts on a power grid system caused by rapid charging, we propose an optimal EV rapid charging navigation strategy based on the internet of things network. The rapid charging price is designed based on the charging power regulation scheme. Both power grid operation and real-time traffic information are considered. The formulated objective of the navigation strategy is proposed to minimize the synthetic costs of EVs, including the traveling time and the charging costs. Simulation results demonstrate the effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessArticle
Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City
Energies 2019, 12(4), 686; https://doi.org/10.3390/en12040686 - 20 Feb 2019
Cited by 2
Abstract
The use of electric vehicles (EVs) is growing in popularity each year, and as a result, considerable demand increase is expected in the distribution network (DN). Additionally, the uncertainty of EV user behavior is high, making it urgent to understand its impact on [...] Read more.
The use of electric vehicles (EVs) is growing in popularity each year, and as a result, considerable demand increase is expected in the distribution network (DN). Additionally, the uncertainty of EV user behavior is high, making it urgent to understand its impact on the network. Thus, this paper proposes an EV user behavior simulator, which operates in conjunction with an innovative smart distribution locational marginal pricing based on operation/reconfiguration, for the purpose of understanding the impact of the dynamic energy pricing on both sides: the grid and the user. The main goal, besides the distribution system operator (DSO) expenditure minimization, is to understand how and to what extent dynamic pricing of energy for EV charging can positively affect the operation of the smart grid and the EV charging cost. A smart city with a 13-bus DN and a high penetration of distributed energy resources is used to demonstrate the application of the proposed models. The results demonstrate that dynamic energy pricing for EV charging is an efficient approach that increases monetary savings considerably for both the DSO and EV users. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Open AccessFeature PaperArticle
Vehicle Electrification: New Challenges and Opportunities for Smart Grids
Energies 2019, 12(1), 118; https://doi.org/10.3390/en12010118 - 29 Dec 2018
Cited by 11
Abstract
Nowadays, concerns about climate change have contributed significantly to changing the paradigm in the urban transportation sector towards vehicle electrification, where purely electric or hybrid vehicles are increasingly a new reality, supported by all major automotive brands. Nevertheless, new challenges are imposed on [...] Read more.
Nowadays, concerns about climate change have contributed significantly to changing the paradigm in the urban transportation sector towards vehicle electrification, where purely electric or hybrid vehicles are increasingly a new reality, supported by all major automotive brands. Nevertheless, new challenges are imposed on the current electrical power grids in terms of a synergistic, progressive, dynamic and stable integration of electric mobility. Besides the traditional unidirectional charging, more and more, the adoption of a bidirectional interconnection is expected to be a reality. In addition, whenever the vehicle is plugged-in, the on-board power electronics can also be used for other purposes, such as in the event of a power failure, regardless if the vehicle is in charging mode or not. Other new opportunities, from the electrical grid point of view, are even more relevant in the context of off-board power electronics systems, which can be enhanced with new features as, for example, compensation of power quality problems or interface with renewable energy sources. In this sense, this paper aims to present, in a comprehensive way, the new challenges and opportunities that smart grids are facing, including the new technologies in the vehicle electrification, towards a sustainable future. A theoretical analysis is also presented and supported by experimental validation based on developed laboratory prototypes. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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Review

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Open AccessReview
Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook
Energies 2020, 13(13), 3352; https://doi.org/10.3390/en13133352 - 30 Jun 2020
Abstract
Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. The benefit of the solution is generally realized as the amount of fuel consumption saved, which by itself represents a challenge to develop the right [...] Read more.
Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. The benefit of the solution is generally realized as the amount of fuel consumption saved, which by itself represents a challenge to develop the right energy management strategies (EMSs) for HEVs. Moreover, meeting the design requirements are essential for optimal power distribution at the price of conflicting objectives. To this end, a significant number of EMSs have been proposed in the literature, which require a categorization method to better classify the design and control contributions, with an emphasis on fuel economy, providing power demand, and real-time applicability. The presented review targets two main headlines: (a) offline EMSs wherein global optimization-based EMSs and rule-based EMSs are presented; and (b) online EMSs, under which instantaneous optimization-based EMSs, predictive EMSs, and learning-based EMSs are put forward. Numerous methods are introduced, given the main focus on the presented scheme, and the basic principle of each approach is elaborated and compared along with its advantages and disadvantages in all aspects. In this sequel, a comprehensive literature review is provided. Finally, research gaps requiring more attention are identified and future important trends are discussed from different perspectives. The main contributions of this work are twofold. Firstly, state-of-the-art methods are introduced under a unified framework for the first time, with an extensive overview of existing EMSs for HEVs. Secondly, this paper aims to guide researchers and scholars to better choose the right EMS method to fill in the gaps for the development of future-generation HEVs. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
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