Vehicles — Open Access Journal

With the development of new energy vehicles, the NVH (Noise, Vibration, Harshness) performance of the permanent magnet synchronous motors (PMSM) for vehicles has attracted more and more attention. The rotor slotting optimization analysis is the critical issue in the NVH performance study of PMSM. In this paper, the theoretical formula of the PMSM radial electromagnetic force is presented. Based on which, the spatial order and frequency order characteristics of the radial force of a 6-pole 36-slot PMSM are analyzed. Firstly, electromagnetic simulation of the motor is carried out, and the specific force components, which may cause an NVH problem, is extracted. Secondly, the harmonics are calculated with a method of freezing the relative magnetic permeability. Thirdly, the motor is optimized by rotor slotting to reduce the amplitudes of these harmonics, and the effect on electromagnetic noise is analyzed in theory and simulation. Finally, the NVH test in original state and after rotor slotting state was performed in the semi-anechoic chamber. The accuracy of the theory and simulation was verified based on the comparison of the measured noise data. This paper provides a new NVH optimization idea, this method can quickly locate the fundamental problem location of electromagnetic NVH, provide a fast channel for electromagnetic NVH optimization from simulation to verification, and improve the optimization efficiency of NVH. Full article

This paper presents a novel framework to enable automatic re-training of the supervisory powertrain control strategy for hybrid electric vehicles using supervised machine learning. The aim of re-training is to customize the control strategy to a user-specific driving behavior without human intervention. The framework is designed to update the control strategy at the end of a driving task. A combination of dynamic programming and supervised machine learning is used to train the control strategy. The trained control strategy denoted as SML is compared to an online-implementable strategy based on the combination of the optimal operation line and Pontryagin’s minimum principle denoted as OOL-PMP, on the basis of fuel consumption. SML consistently performed better than OOL-PMP, evaluated over five standard drive cycles. The EUDC performance was almost identical while on FTP75 the OOL-PMP consumed 14.7% more fuel than SML. Moreover, the deviation from the global benchmark obtained from dynamic programming was between 1.8% and 5.4% for SML and between 5.8% and 16.8% for OOL-PMP. Furthermore, a test-case was conducted to emulate a real-world driving scenario wherein a trained controller is exposed to a new drive cycle. It is found that the performance on the new drive cycle deviates significantly from the optimal policy; however, this performance gap is bridged with a single re-training episode for the respective test-case. Full article

Of all driving functions, one of the critical maneuvers is the lane merge. A cooperative Nonlinear Model Predictive Control (NMPC)-based optimization method for implementing a highway lane merge of two connected autonomous vehicles is presented using solutions obtained by the direct multiple shooting method. A performance criteria cost function, which is a function of the states and inputs of the system, was optimized subject to nonlinear model and maneuver constraints. An optimal formulation was developed and then solved on a receding horizon using direct multiple shooting solutions; this is implemented using an open-source ACADO code. Numerical simulation results were performed in a real-case scenario. The results indicate that the implementation of such a controller is possible in real time, in different highway merge situations. Full article

In order to improve the fuel economy of vehicles, based on the automated mechanical transmission (AMT), a plug-in hybrid electric vehicle (PHEV) hybrid transmission for low-end multi-purpose vehicles (MPVs) is developed. To obtain the statistics of the best-selling models, we took several best-selling models in the Chinese market as the research object to study the relationship between power demand, energy demand, weight, and cost. The power requirements and energy requirements of PHEVs are decoupled. According to the decoupled theory, a single-motor parallel scheme based on the AMT is adopted to develop a PHEV hybrid transmission. In the distribution of engine and motor power, the engine just needs to meet the vehicle’s constant driving power, and the backup power can be provided by the motor, which means we can use an engine with a smaller power rating. The energy of short-distance travel is mainly provided by the motor, which can make full use of the battery, reducing the fuel consumption. The energy of long-distance travel is mainly provided by the engine, which can reduce the need for battery capacity. The working modes of the electrified mechanical transmission (EMT) are proposed, using P3 as the basic working mode and setting the P2 mode at the same time, and the gear ratios are designed. Based on the above basic scheme, two rounds of prototype development and assembling prototype vehicles for testing are carried out for the front-engine-front-drive (FF) layout. The test results show that the vehicle’s economy has been improved compared to the unmodified vehicle, and the fuel-saving rate of 100 kilometers has been achieved at 35.18%. The prototype development and the vehicle matching verify the effectiveness of the new configuration based on AMT. Full article

For decades, drivers and fleet managers have been impacted by the instability of fuel prices, the need to save resources and the duty to meet and attain environmental regulations and certifications. Aiming to increase performance and efficiency and reduce emissions and mileage costs, plug-in electric vehicles (PHEVs) have been pointed out as a viable option, but there are gaps related to tools that could improve the numerous existing conventional vehicles. This study presents the design of an aftermarket hybridization kit that converts a vehicle originally driven by a combustion engine into a PHEV. To achieve this goal, an optimization was conducted with the objective of decreasing the cost (regarding fuel consumption and battery charging) to perform a local driving cycle, while attenuating the tailpipe emissions and reducing the battery mass. The torque curves of the electric motors, the battery capacity, the parameters for a gear shifting strategy and the parameters for a power split control were the design variables in the optimization process. This study used the Campinas driving cycle, which was experimentally obtained in a real-world driving scenario. The use of a local driving cycle to tune the design variables of an aftermarket optimization kit is important to achieve a customized product according to the selling location. Among the optimum solutions, the best trade-off configuration was able to decrease the mileage cost in 22.55%, and reduce the tailpipe emissions by 28.4% CO, 33.55% NOx and 19.11% HC, with the addition of a 137 kg battery. Full article

As a crucial output component, a clutch pressure sensor is of great importance on monitoring and controlling a whole transmission system and a whole vehicle status, both of which play important roles in the safety and reliability of a vehicle. With the help of fault diagnosis, the fault state prediction of a pressure sensor is realized, and this lays the foundation for further fault-tolerant control. In this paper, a fault diagnosis method of Dual Clutch Transmission (DCT) is designed. Firstly, a Variable Force Solenoid (VFS) valve model is established. A feed-forward input system is added to correct the first-order inertial link of the sensor on the second step. Finally, the parameters of the established system model are identified by using the measured data of the actual transmission and the Genetic Algorithm (GA). An identified model is then used for designing a fault observer. The constant output faults of 0, 3, and 5 V, pulse fault, and bias fault that enterprises are concerned with are selected to simulate and verify the fault observer under four different operating conditions. The results show that the designed fault observer has great fault diagnosis performance. Full article

Transmission system power losses influence the efficiency of hybrid powertrains. Well-established parallel-hybrid-electric powertrains employ conventional transmissions that can be treated as single-input-single-output (SISO) systems. Novel parallel-hybrid-electric powertrains, which are not based on conventional transmissions, can increase the systems potential but increase the complexity as the transmission becomes a multiple-input-multiple-output (MIMO) system. For these MIMO-transmission systems, the losses can strongly depend on the selected transmission mode and on the input torques of the power sources. This paper presents a method to automatically model the power losses of such MIMO-transmission systems. This method consists of a mathematical analysis and a design analysis, and obtains the transmission power losses as a function of the selected transmission mode, the rotational speed of the wheels, and the torques of the power sources. The model includes gear meshing losses, gear churning losses, and bearing losses. Furthermore, an extended control strategy is proposed to ensure local optimality including the consideration of the multidimensional transmission power loss characteristics. A case study is presented to demonstrate the developed methods, and shows that the inclusion of the transmission losses in the powertrain model and control strategy can be considered relevant for the simulative assessment of novel parallel-hybrid-electric powertrains. Full article

This paper presents study of a multi-slice subdomain model (MS-SDM) for persistent low-frequency sound, in a wheel hub-mounted permanent magnet synchronous motor (WHM-PMSM) with a fractional-slot non-overlapping concentrated winding for a light-duty, fully electric vehicle applications. While this type of winding provides numerous potential benefits, it has also the largest magnetomotive force (MMF) distortion factor, which leads to the electro-vibro-acoustics production, unless additional machine design considerations are carried out. To minimize the magnetic noise level radiated by the PMSM, a skewing technique is targeted with consideration of the natural frequencies under a variable-speed-range analysis. To ensure the impact of the minimization technique used, magnetic force harmonics, along with acoustic sonograms, is computed by MS-SDM and verified by 3D finite element analysis. On the basis of the studied models, we derived and experimentally verified the optimized model with 5 dBA reduction in A-weighted sound power level by due to the choice of skew angle. In addition, we investigated whether or not the skewing slice number can be of importance on the vibro-acoustic objectives in the studied WHM-PMSM. Full article

This study presents a comparison of the common Child Restraint Systems (CRS) which reduces the value of dynamic loads affecting the child’s body during car accidents. The analyzed systems were: child seats, booster seats, and straps—adjustable vehicle seat belts adapted to children’s stature. The effectiveness of the analyzed devices was assessed on the basis of experimental tests carried out in the accredited laboratory approving the Child Restraint Systems. The tests were carried out in accordance with the new Regulation No. 129 UN/ECE. The authors examined whether the tested devices meet the guidelines of the new Regulations No. 129 despite approval in accordance with Regulation No. 44. Based on the research results, better safety parameters of some new solutions dedicated to children’s safety could be observed. Almost all the selected CRS met requirements stated in Regulation No. 129. The only exception was for abdominal pressure in one of the tested devices. Head Resultant Acceleration in tested devices was 14.7–39.0% less than the limit determined in Regulation No. 129 whereas Chest Resultant Acceleration was 17.4–37.6% less. Abdominal pressure was 46.4–81.4% beneath the limit (apart from one case which did not meet the requirements). The HPC parameter (Head Performance Criterion) was 45.4–74.5% less. The final results show that there are still some possibilities for improving the safety of young vehicle passengers. Full article

Reliability assessment plays a significant role in mechanical design and improvement processes. Uncertainties in structural properties as well as those in the stochatic excitations have made reliability analysis more difficult to apply. In fact, reliability evaluations involve estimations of the so-called conditional failure probability (CFP) that can be seen as a regression problem taking the structural uncertainties as input and the CFPs as output. As powerful ensemble learning methods in a machine learning (ML) domain, random forest (RF), and its variants Gradient boosting (GB), Extra-trees (ETs) always show good performance in handling non-parametric regressions. However, no systematic studies of such methods in mechanical reliability are found in the current published research. Another more complex ensemble method, i.e., Stacking (Stacked Generalization), tries to build the regression model hierarchically, resulting in a meta-learner induced from various base learners. This research aims to build a framework that integrates ensemble learning theories in mechanical reliability estimations and explore their performances on different complexities of structures. In numerical simulations, the proposed methods are tested based on different ensemble models and their performances are compared and analyzed from different perspectives. The simulation results show that, with much less analysis of structural samples, the ensemble learning methods achieve highly comparable estimations with those by direct Monte Carlo simulation (MCS). Full article

For many manufacturers, hybridization represents an attractive solution for reducing the energy consumption of their vehicles. However, electrification offers a wide range of possibilities for implementing powertrain concepts. The concepts can differ regarding their mechanical complexity and the required power of the electrical machines. In this article, drive concepts that differ in their functionality and drive train topology are compared. Based on requirements for the C, D, and E segment, the mechanical and electrical effort of the concepts is analyzed. The results show that the mechanical effort in the C segment can be reduced as long as the electrical effort is increased. In case of higher vehicle segments, the electrical effort can increase considerably, making concepts with increased mechanical complexity more suitable. The driving performance and efficiency in hybrid operation are evaluated via simulation. The results show that the difference of acceleration times in hybrid operation between a charged and discharged battery is lower for mechanically complex concepts. At the same time, they achieve lower CO₂ emissions. Therefore, these concepts represent a better compromise regarding performance and efficiency. Despite lower transmission efficiencies in hybrid operation, they achieve conversion qualities similar to simpler concepts and lower emissions with lower electrical effort. Full article

We present an optimization model for the passenger car vehicle fleet transition—the time-dependent fleet composition—in Germany until 2050. The goal was to minimize the cumulative greenhouse gas (GHG) emissions of the vehicle fleet taking into account life-cycle assessment (LCA) data. LCAs provide information on the global warming potential (GWP) of different powertrain concepts. Meta-analyses of batteries, of different fuel types, and of the German energy sector are conducted to support the model. Furthermore, a sensitivity-analysis is performed on four key influence parameters: the battery production emissions trend, the German energy sector trend, the hydrogen production path trend, and the mobility sector trend. Overall, we draw the conclusion that—in any scenario—future vehicles should have a plug-in option, allowing their usage as fully or partly electrical vehicles. For short distance trips, battery electric vehicles (BEVs) with a small battery size are the most reasonable choice throughout the transition. Plug-in hybrid electric vehicles (PHEVs) powered by compressed natural gas (CNG) emerge as promising long-range capable solution. Starting in 2040, long-range capable BEVs and fuel cell plug-in hybrid electric vehicles (FCPHEVs) have similar life-cycle emissions as PHEV-CNG. Full article

Vehicles’ braking is a key factor towards safer driving. In particular, tyre–pavement friction is connected with both industry and infrastructure requirements in terms of tyre characteristics and frictional properties of pavement surfaces respectively that both contribute to safe braking. For this reason, tyre–pavement friction is considered as one of the most pressing emergencies in roadway assets in order to reduce skidding related accidents. At the same time, sustainability aspects have been raised in modern infrastructure engineering. Hence, an issue is introduced on how sustainable materials used for pavement construction may contribute to tyre–pavement and consequently vehicles’ braking. For this reason, a laboratory process is developed to investigate the frictional properties of several utilized in pavement wearing courses including both traditional and sustainable materials (reacted activated rubber—RAR and reclaimed asphalt pavement—RAP). Environmental conditions (seasonal temperature changes, rainfall effect and contamination caused by dust formation) are simulated in the laboratory and vehicles’ braking is investigated using the British Pendulum Tester (BPT). Results provide a good explanation for the vehicles’ braking ability under the investigated conditions for both traditional and sustainable materials. Ultimately, it is proved that asphalt mixture types with RAR modifier or RAP material exhibit a satisfactory performance towards providing a safe road surface for the moving vehicles. Full article

Intelligent Transportation Systems (ITS), such as Green Light Optimal Speed Advisory (GLOSA) systems, can be used to reduce the energy consumption in modern vehicles. In particular, GLOSA systems provide driving strategies that can decrease both energy consumption and travel time. In this paper, we present a new method to calculate the optimal driving speeds based on traffic light data. To this end, a detailed formulation for the optimization problem is presented for a multi-segment route, based on an electric vehicle (EV) and traffic light models in an urban environment. Since this formulation results in a nonconvex optimization problem, a relaxation procedure is applied with a low calculation time. By using this procedure, a dynamic real-time speed advisory algorithm is developed. Numerical simulations showed improved performance over benchmark techniques. In particular, the proposed Dynamic-GLOSA solution’s performance was shown to be very close to that with a brute-force optimal solution but with a much shorter calculation time and has significant potential for energy saving. Full article

Inside the passenger cabin of modern cars, lower noise levels from quieter engines make road noise more dominant. The main transfer path for road noise below 300 Hz into the car is the suspension. Suspension layouts are mainly determined by driving dynamics, but their influence on road noise is not in focus. Layout design changes for driving dynamics in the early development phase require the modification of structural dynamics Finite Element (FE) models used to predict interior acoustics. This manual modification makes acoustical effects from layout design changes difficult to predict. In the following article, we present a method to adapt suspension FE models automatically to suspension layout changes. This allows an automatic optimization of the suspension layout regarding road noise. As an example, a rear axle suspension layout is modified to decrease road noise between 60 and 90 Hz by moving the connection point between the track rod and the knuckle. Full article

This paper presents the development of a control strategy for a fuel cell and supercapacitor hybrid power system for application in a city driving bus. This aims to utilise a stable fuel cell power output during normal operation whilst allowing variations to the power output based on the supercapacitor state-of-charge. This provides flexibility to the operation of the system, protection against over-charge and under-charge of the supercapacitor and gives flexibility to the sizing of the system components. The proposed control strategy has been evaluated using validated Simulink models against real-world operating data collected from a double-decker bus operating in London. It was demonstrated that the control strategy was capable of meeting the operating power demands of the bus and that a wide range of degrees of hybridisation are viable for achieving this. Comparison between the degree of hybridisation proposed in this study and those in operational fuel cell (FC) hybrid buses was carried out. It was found that the FC size requirement and FC variation can be significantly reduced through the use of the degree of hybridisation identified in this study. Full article

Lithium-ion polymer batteries currently are the most popular vehicle onboard electric energy storage systems ranging from the 12 V/24 V starting, lighting, and ignition (SLI) battery to the high-voltage traction battery pack in hybrid and electric vehicles. The operating temperature has a significant impact on the performance, safety, and cycle lifetime of lithium-ion batteries. It is essential to quantify the heat generation and temperature distribution of a battery cell, module, and pack during different operating conditions. In this paper, the transient temperature distributions across a battery module consisting of four series-connected lithium-ion polymer battery cells are measured under various charging and discharging currents. A battery thermal model, correlated with the experimental data, is built in the module-level in the ANSYS/Fluent platform. This validated module thermal model is then extended to a pack thermal model which contains four parallel-connected modules. The temperature distributions on the battery pack model are simulated under 40 A, 60 A, and 80 A constant discharge currents. An air-cool thermal management system is integrated with the battery pack model to ensure the operating temperature and temperature gradient within the optimal range. This paper could provide thermal management design guideline for the lithium-ion polymer battery pack. Full article

One of the most common approaches in modern engineering research, including vehicle dynamics, is to formulate an accurate, but typically complex, mathematical model of a system or phenomenon and then use a software package to solve it. Typically, the solution is obtained in the form of a large data set, which may be difficult to analyse and interpret. This paper represents a purely theoretical analysis of a special case of vehicle longitudinal motion. Starting from a simplified mathematical model, a set of transcendental equations was derived that represents the exact solution of the model (i.e., in a closed form). The equations are analysed and interpreted in terms of what is their physical meaning. Although the equations derived here have only limited application in studying real world problems, due to the simplicity of the mathematical model, they offer a deeper insight into the nature of vehicle longitudinal motion. Full article

The increased temperature of the rail wheels due to tread braking causes changes in the wheel material properties. This article considers the dynamic wheel material properties in a wheel wear evolution model by synergistically combining a multi-body dynamics vehicle model with a finite element heat transfer model. The brake power is estimated from the rail-wheel contact parameters obtained from vehicle model and used in a finite element model to estimate the average wheel temperature. The wheel temperature is then used for wheel wear computation and the worn wheel profile is fed to the vehicle model, thereby forming a recursive simulation chain. It is found that at a higher temperature, the softening of the rail-wheel material increases the rate of wheel wear. The most affected dynamic performance parameter of the vehicle is found to be the critical speed, which reduces sharply as the wheel wear exceeds a critical limit. Full article