Forthcoming articles

International Journal of Vehicle Performance

International Journal of Vehicle Performance (IJVP)

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International Journal of Vehicle Performance (19 papers in press)

Regular Issues

  • Optimization of the energy efficiency of a hybrid vehicle powertrain   Order a copy of this article
    by Ali Salah Mourad, Benhadj Braiek Naceur 
    Abstract: Nowadays fossil fuels are the main source of energy in all areas. This energy has become less abundant, more expensive and much more polluting. To minimize fuel consumption, automakers are committed to develop new more efficient engine motorization system architectures. The substitution of the conventional thermal engine by a hybrid powertrain provides an additional degree of freedom to manage the energy flow between an electrical branch and a thermal branch to consume less fuel. Note that parallel architecture offers the best compromise between simplicity of design and energy efficiency, relative to other architectures and in particular serial architecture and mixed architecture. The optimization of fuel consumption relative to a known driving history such as (NEDC) does not solve the problem of optimization of fuel consumption when driving conditions are unknown in advance (actual operation of a vehicle). This work treats the energy modelling of a parallel architecture powertrain and proposes a new algorithm for optimizing fuel consumption, which is independent of the route taken by the vehicle. For this goal, we start by designing two energy models that express the instantaneous overall efficiency of the vehicle powertrain. Next, we develop the fuel optimization algorithm. Compared to the internal combustion engine of a conventional vehicle, the hybrid vehicle of parallel architecture shows, via simulations, a significant energy efficiency gain.
    Keywords: Parallel hybrid vehicle; Powertrain; Energy management; optimal control strategy; instantaneous optimization of energy flow.

  • Evaluation of Worldwide Harmonized Light Vehicles Test Procedure for Electric Vehicles using Simulation   Order a copy of this article
    by Jia Xian Teoh, Chew Kuewwai 
    Abstract: With the introduction of the Worldwide Harmonized Light Vehicle Test, an all-new drive cycle proposed by UNECE, is being set to standardize the global drive cycle testing procedure in determining emission compliance and energy and fuel consumption. This paper aims to evaluate the performance and the effect of the new driving cycle on different electric vehicles, compared with other commonly used regulatory drive cycles such as NEDC, FTP 75 and JC08. Using Matlab ADVISOR simulation, different vehicles namely, a hatchback of Nissan Leaf 2016, a sedan of Tesla Model S 60 and a low power electric vehicle of Mahindra E2O Plus have been simulated and investigated. Among the various driving cycles, the Worldwide Harmonized Light Vehicles Test Procedure, WLTP Test Cycle consumes the highest energy per unit distance to decently sized vehicles. This is consistent with the objectives of the new driving cycle in obtaining more realistic results. Nevertheless, the low powered electric vehicle is found to perform differently in the WLTP Test Cycle. As the performance of lower powered motor is limited, the strategic low-speed operation of the vehicle during the drive cycle can result in higher power consumption pattern. The paper also encompasses a method to simplify the complex modelling of the vehicle for the drive cycles simulation, while maintaining sufficient accuracy in its final emission results.
    Keywords: Worldwide Harmonized Light Vehicles Test Procedure (WLTP); Driving Cycle Standards; Electric Vehicle; Vehicle Test Procedures; ADVISOR.

  • Load torque estimation for an automotive electric rear axle drive by means of virtual sensing using Kalman filtering   Order a copy of this article
    by Robert Kalcher, Katrin Ellermann, Gerald Kelz 
    Abstract: Load torque signal information in hybrid or battery electric vehicles would be beneficial for control applications, extended diagnosis or load spectrum acquisition. Due to the high cost of the sensor equipment and because of the inaccuracies of state-of-the-art estimation methods, however, there is currently a lack of accurate load torque signals available in series production vehicles. In response to this, this work presents a novel model-based load torque estimation method using Kalman filtering for an electric rear axle drive. The method implements virtual sensing by using measured twist motions of the electric rear axle drive housing and appropriate simulation models within a reduced-order unscented Kalman filter. The proposed method is numerically validated with help of sophisticated multibody simulation models, where influences of hysteresis, torque dynamics, road excitations and several driving manoeuvres such as acceleration and braking are analysed.
    Keywords: load torque estimation; electric rear axle drive; virtual sensing; Kalman filtering; unscented Kalman filter; UKF; reduced-order unscented Kalman filter; ROUKF; hybrid electric vehicles; HEV; battery electric vehicles; BEV; multi-body simulations; MBS; vehicle systems modelling.

  • Deep reinforcement learning-based energy management strategy for hybrid electric vehicles   Order a copy of this article
    by Shiyi Zhang, Jiaxin Chen, Bangbei Tang, Xiaolin Tang 
    Abstract: In recent years, with the development of new energy vehicle industry, the development potential of hybrid electric vehicles (HEVs) is increasing. As one of the key technologies, energy management strategy (EMS) has always been a hot research area for hybrid electric vehicles. This paper proposed a Deep Q-Network (DQN) based EMS for a parallel HEV. Simulation results after training show that, compared with the EMS based on dynamic programming (DP), the DQN-based EMS can achieve 8.38% of the fuel consumption gap while the calculation time is only 12.5%. By the computational advantage of neural network, the average output time of an action in each state is 1ms, which has the potential for real-time applications. Since the final EMS is parameterized and fitted by deep neural networks of deep learning, it is necessary to find further methods for the actual experimental scheme instead of simulation in the future.
    Keywords: Hybrid electric vehicle; learning-based energy management strategy; deep reinforcement learning.

  • Racing Line Optimisation for an Advanced Driver Assistance System   Order a copy of this article
    by Falk Salzmann, Sofiane Gadi, Ingmar Gundlach 
    Abstract: This paper deals with an accurate, robust and efficient optimisation method for time optimal path planning on circular tracks. Starting with a general description of the problem, suitable method domains for time-optimal path planning are qualified. In terms of reproducibility and accuracy, we propose an algorithm combining a model and a policy-based method which takes car, track and driving data gathered from connected cars into account. Hence, it can provide a consistently learning as well as a sufficient constant time-optimal racing line on worldwide race tracks for different driver assistance purposes. We evaluated the calculated racing lines with respect to heuristic criteria like curve cutting behaviour and by comparing them to ones driven by professional race drivers.
    Keywords: driver assistance; connected car; reinforcement learning; trajectory optimization; vehicle dynamics.

    Abstract: In the current age, the automobile industry has been facing multiple challenges like stringent emission norms, surging fuel prices, and customer demand for better fuel efficiency. So they are finding all possibilities by which they can satisfy all the requirements. In case of available options for transmission systems, Automatic and Automatic manual transmission systems (with single clutch) are in demand despite manual transmission returning a better fuel efficiency, due to ease of driving in traffic. In addition, these automatic manual transmission systems also lack in performance and driving comfort due to jerky shifts, as compared to the manual transmission systems. To overcome these challenges, dual-clutch transmission systems are being used. This is also a type of Automatic manual transmission system but has two clutches in operation as compared to one in others. There are two shafts on which the gears are mounted such that usually odd gears are on one shaft and even gears are on another. This allows the gear to be shifted without disengaging the drivetrain from the engine. The lag observed in single clutch automatic manual transmission systems while disengaging/engaging the clutch is avoided and the vehicle accelerates uniformly. This gives the advantage to offer better fuel efficiency, performance, and better ride comfort. This literature work focuses on the evolution, classification, components, lubrication technologies, controllers, and control strategies involved in the operation, existing systems with case studies, and comparison of dual-clutch transmission with other types of systems.
    Keywords: Dual clutch transmission; automatic manual transmission; transmission fluids; Automotive transmission systems; automatic manual transmission controllers.

Special Issue on: Recent Advances in Energy-efficient Research for Vehicle Performance Improvement

  • A new model predictive torque control strategy for Permanent Magnet Synchronous Hub Motor of EVs   Order a copy of this article
    by Long Chen, Hao Xu, Xiaodong Sun 
    Abstract: This paper presents an optimal control strategy for a permanent magnet synchronous hub motor (PMSHM) of EVs drive using three voltage vectors. First, in order to simultaneously control torque and flux excellently, three voltage vectors including two active vectors and one zero voltage vector are selected. Second, the duration of the three voltage vectors in one period is calculated by the principle of simultaneous deadbeat control of torque and flux. Moreover, the cost function which eliminates the weight coefficient is proposed to reduce the amount of calculation. Finally, the proposed method is compared with the one- and two-vector-based model predictive torque control (MPTC) methods both in simulation and experiment. It is found that the proposed three-vector-based MPTC can obtain better performance such as smaller torque ripple and current total harmonic distortion (THD) both in steady and dynamic state.
    Keywords: Model predictive torque control (MPTC); permanent magnet synchronous hub motor (PMSHM); three voltage vectors.

  • Study on Comprehensive Performance of Ni-MH Power Battery Used in HEV at Different Temperatures   Order a copy of this article
    by Xiang Chen 
    Abstract: The safety concern of the lithium-ion battery drives major motor company such as Toyota to consider the nickel-hydrogen (Ni-MH) battery in their HEV (e.g. Prius). However, current understanding of the cycling life and SOC (State of Charge) estimate of Ni-MH battery in the HEV is still limited due to its insignificant market share. Thus, this study carries a comprehensive investigation on the influences of the key environmental and operating parameters on SOC and cycling life of the Ni-MH battery. Notably, the Ni-MH cells were tested through loading the actual road spectrum with different temperatures (25/35/45?) being used to identify the impacts based on the actual work condition. Other factors including discharge current and depth of discharge are operated at 15.5A and 10% by average, respectively. In addition, to obtain the battery polarization characteristics under different temperatures and SOCs, multiple trials have been performed to obtain the OCV (open circuit voltage)~SOC curves at different temperatures under the 1-C rate of charging/discharging. The investigation results show that the battery degradation is accelerated at the upper-end level of the operating temperature range. The capacity decay compared to initial capacity is increased by a slight 2.46% at 45?, which demonstrates an excellent cycling performance of the Ni-MH battery. The battery polarization effect is found to be correlated to the charging and discharging processes. The lower the temperature is, the greater the polarization effect can be observed as a more salient OCV difference presents between charging and discharging. The polarization effect almost disappeared after 3 hours resting according to the results in this study. In summary, this study presents a comprehensive factor analysis needed to achieve a reliable SOC estimate for the Ni-MH based HEV.
    Keywords: Ni-MH battery; hybrid electric vehicle; polarization effect; Cycling life; SOC estimate.

  • Research on Modeling and Simulation of single-mode power split hybrid system   Order a copy of this article
    by Aihua Chu, Xiang Chen, Yinnan Yuan, Tong Zhang, Huijun Cheng, Wenran Geng 
    Abstract: Aiming at an optimized single-mode compound power split hybrid system, the main operating mode of the hybrid system and the torque control strategy were developed in this paper. LMS/AMESim was used to establish the plant model of the vehicle as well as the key components of the hybrid system, while the vehicle control model was established in Matlab/Simulink. Both control model and plant model were integrated in the same environment through co-simulation technology. In addition, the fuel economy of a certain SUV under the NEDC road spectrum was simulated by the co-simulation model, and the simulation results were compared with the experimental results on the auto chassis dynamometer. The results have shown that in the HEV operation mode, the electric energy consumption of the battery in experiment was 0.6241kWh well agreed with the value of 0.6220kWh through simulation, achieving only 0.33% deviation. Moreover other two key indicators, the SOC change and regenerative braking energy recovery, were found to be -4.8% and 694.90kJ, respectively, in the simulation. These results are strikingly compatible to the experimental values as well. The deviations are 0.7% and 3.8% respectively. The results demonstrated that the established simulation model is an accurate reflection of the physical reality under different road spectrum conditions. Application of the model can greatly reduce the difficulty of control strategy design and improve the efficiency of vehicle development.
    Keywords: hybrid electric vehicle; power-split system; CHS2800; co-simulation; vehicle controller model; AMESim; MATLAB/Simulink.

  • The effect of peppermint odor on fatigue and vigilance in conditional automated vehicle   Order a copy of this article
    by Qiuyang Tang, Gang GUO, Meng Jin Zeng 
    Abstract: Drivers in conditionally automated vehicles have been found to become fatigued easier than manual drivers, and the risk of accidents increased due to the decrease in vigilance. Olfactory stimulation is a promising method to counterbalance fatigue and increase vigilance. However, little is known about the effect of peppermint odor on relieving fatigue and increasing vigilance during automated driving. Therefore, to better understand the effect of peppermint odor stimulation during automated driving, a driving simulator study with 34 participants was conducted. Subjective and objective variables were compared between two conditions: with peppermint odor and placebo (air). The results of the study indicated that the fatigue levels of drivers decreased after the release of peppermint odor. The indicators of reaction time and ocular variables supported that the drivers` vigilance increased during the peppermint stimulation. In conclusion, peppermint odor has a positive effect on relieving fatigue and increasing vigilance.
    Keywords: Fatigue countermeasures; Peppermint odor; Driver vigilance; Eye movement.

  • Energy Management Optimal Strategy of FCHEV Based on The Radau Pseudospectral Method   Order a copy of this article
    by Yanwei Liu, Yuzhong Chen, Zhenye Li, Kegang Zhao 
    Abstract: Energy management of the fuel cell hybrid electric vehicle (FCHEV) is a significant study area with respect to improving FCHEVs dynamic and efficiency performance and durability. Radau Pseudospectral Method (RPM)-based optimal control of energy management of FCHEV is introduced to optimize the fuel cells lifetime by means of reducing its performance degradation. To utilize the RPM, both state variable and control variable are approximated by the global interpolation polynomial, and then differential equation of state variable is approximated by the derivative of interpolation polynomial. Accordingly, the optimal control problem is transformed into nonlinear problem to be solved. The fuel cells performance degradation which refers to fuel cells voltage decline is selected as objective function. The results of optimal control in NEDC show that battery with larger capacity is more beneficial than smaller one for reducing the fuel cells performance degradation, with the total time of large load change of the fuel cell reducing. The RPM is an effective way to optimize not only the fuel cells lifetime but other objectives to energy management.
    Keywords: energy management; fuel cell vehicle; electric vehicle; Radau Pseudospectral Method; optimal strategy.

  • Control Strategy of Genetic algorithm for a Hybrid Electric Container Loader   Order a copy of this article
    by Jian Li, Hong Shu, Zhien Xu, Weizhou Huang 
    Abstract: Hybrid electric container loaders are used for cargo transportation in aviation airports, which have characteristics of relatively complicated operating conditions and large load changes. How to ensure that under various loads, battery state of charges (SOCs) and temperatures the loader runs in the high efficient zone, the SOC and temperature of battery are maintained within a reasonable range is an important issue that the control strategy needs to solve. A genetic algorithm is applied to optimize the control parameters of the hybrid loader. The optimal control parameters are the charging torque limit, the discharging torque limit, the generator charging torque, the motor discharging torque, the engine speed at high and low load, and the battery high SOC threshold. The optimization target is to take the minimum equivalent fuel consumption under loader cycle conditions, and maintain the battery SOC sustain or reach the optimal range. The optimal control parameters of the loader under multiple loads, battery temperatures and initial SOCs were optimized offline by using genetic algorithms. Finally, a multidimensional response surface model for control parameters was established by a response surface method. The simulation shows that under various loads, battery temperatures and initial SOCs, the fuel saving of the hybrid loader is significant, the battery maintains the charge sustain or reaches within the optimal range, the battery temperature rising is kept within a reasonable range, and the battery charge and discharge rate is controlled within 1C.The fuel consumption of the hybrid electric loader is reduced by more than 20% compared with the traditional loader under the full load conditions and the initial SOC in the range of 0.6-0.8.Compared with the original calculation model optimized by genetic algorithms and the dynamic programming control strategy, it was verified that the calculation accuracy and fuel saving significance of the response surface model for control parameters.
    Keywords: Hybrid Electric Vehicles; Control Strategy; Genetic Algorithm; Response Surface.

  • Research on regenerative braking strategies for hybrid electric vehicle by co-simulation model   Order a copy of this article
    by Han Guo, Jianwu Zhang, Wenran Geng, Huijun Cheng, Haisheng Yu 
    Abstract: Regenerative braking is an important factor in improving hybrid electric vehicle fuel economy. This paper presents the simulation modelling of a power-split hybrid electric vehicle with different regenerative braking strategies. A co-simulation model is used to enhance the simulation capability for the hybrid vehicle performance and development of control strategy. AMESim is used to model the complex physical components including engine, transmission, motors, battery and hybrid vehicle, and the physical model is integrated with control model established by MATLAB/Simulink, which is required to operate the vehicle and the regenerative braking system through standard drive cycles. Simulation results show that a regenerative braking control strategy can recuperate significant amounts of energy. Vehicle fuel economy in EV and HEV modes is improved significantly by coupling the proposed regenerative braking strategy.
    Keywords: hybrid electric vehicle; regenerative braking; energy management; AMESim; MATLAB/Simulink.

  • Potential and Challenges to improve vehicle energy efficiency via V2X: Literature Review   Order a copy of this article
    by Kai Yang, Yanjun Huang, Yechen Qin, Chuan Hu, Xiaolin Tang 
    Abstract: With the development of intelligent transportation system, V2X information offers great opportunities to promote the energy efficiency of vehicles. This paper systematically elaborates the state of art which focuses on improving the energy efficiency using the V2V (vehicle to vehicle), V2I (vehicle to infrastructure), V2N (vehicle to network) and V2G (vehicle to grid) technology. Firstly, V2V technology applied in energy management of single and vehicular platoon is investigated. Secondly, eco-driving for connected vehicles using V2I information is studied. Thirdly, the potential of enhancing the energy efficiency by the V2N communication between vehicles and network is analyzed as well. Fourthly, the utilization of V2G technology to increase the energy efficiency of smart grid is presented. Finally, the challenges are suggested to facilitate the application of V2X technology to the enhancement of energy efficiency.
    Keywords: vehicle energy efficiency; V2X; V2V; V2I; V2N; V2G.

Special Issue on: Recent Advancements in Commercial Vehicle Roll Dynamics Studies

  • Active Trailer Braking Control for Car-Trailer Combination Based on Multi-objective Fuzzy Algorithm   Order a copy of this article
    by Pengwei Su, Xing Xu, Feng Wang, Bin Wang, Jie Mi 
    Abstract: In order to improve the braking stability and path following performance of trailer under steering and braking conditions, a differential braking control method is proposed. Considering the electromechanical coupling characteristic of electromagnetic brake, a 6-DOF car-trailer (CT) combination dynamics model is established. A hierarchical control frame is proposed, the upper controller determines the additional yaw moment based on multi-objective fuzzy (MOF) control algorithm with yaw rate and hinge angle as control objects. The lower braking force distribution controller is designed with the rules to determine left and right braking torque, the electromagnetic brake gets the corresponding current to realize differential brake. A joint simulating model with TruckSim and Simulink is built, the simulation results show that the control strategy proposed in this paper effectively improves the braking stability of trailer. Compared with no differential braking control, the yaw rate and lateral acceleration are reduced, the hinge angle is closer to the ideal target under MOF control. Finally, real CT test is put forward to verify the accuracy of the model and the effectiveness of the control strategy.
    Keywords: car-trailer; differential braking; yaw rate; hinge angle; multi-objective fuzzy algorithm; braking force distribution controller.

  • Effect of Off-centered Loading on Roll Stability of Multi-trailer Trucks   Order a copy of this article
    by Yang Chen, Xiaohan Zheng, Zichen Zhang, Mehdi Ahmadian 
    Abstract: The effect of partial loading on the wheel tip-up and rollover stability of 28-ft A-double tractor-trailers that are logistically attractive to the U.S. package carriers is studied using TruckSim
    Keywords: off-centered loading; 28-ft A-double; commercial vehicle; roll stability; rollover; tip-up; J-turn; load transfer ratio; critical rollover speed; static stability factor.

  • GA Tuned H Infinity Roll Acceleration Controller Based on Series Active Variable Geometry Suspension on Rough Roads   Order a copy of this article
    by Shayan Nazemi, Masoud Masih-Tehrani, Morteza Mollajafari 
    Abstract: In this paper, a type of vehicle variable-geometry suspension, named, Series Active Variable Geometry Suspension is used on a GT car under turning event with crosswind forces on random Rough Road classes D and C in order to keep control of the vehicle\'s Roll Angle and Roll Angle Acceleration to prevent the car from transferring too much force into the passengers and the car\'s suspension links, also, to keep the tires Road Holding and not to let them leave the ground and prevent rollover accidents. To do so, first, the vehicle goes under modelling. The vehicle\'s full car dynamics are modeled. A Genetic Algorithm H? control synthesis would be applied to the system which goal objective is to control the vehicle\'s roll angle acceleration motion. Then, the maneuver fit for the goals is designed, which is turning with the forward speed of 100 km/h and an additional crosswind with the speed of 150 km/h that produces a maximum lateral acceleration of 0.4 m/s which is transferred to the vehicle\'s model. After that, the simulation is thoroughly discussed, it will be shown that the roads are generated using ISO8608, and random road classes D and C are produced. For comparison purposes, a Genetic Algorithm PID controller is designed so that the performance of the H? control synthesis would be better judged. The H? control synthesis succeeded in improving the vehicle\'s roll angle and rollover index up to 85% and the vehicle\'s roll angle acceleration up to 13% in comparison with the PID controller.
    Keywords: H? Controller; Series Active Variable Geometry Suspension; SAVGS; Genetic Algorithm; Full-Car Modelling; Rollover Control; Random Rough Road.

  • Roll stability enhancement in a full dynamic ground-tour vehicle model based on series active variable-geometry suspension   Order a copy of this article
    by Amin Najafi, Masoud Masih-Tehrani 
    Abstract: Today, given the importance of vehicle rollover event and the high number of accidents in this area, in this paper, an attempt is made in the field of rollover prevention of the ground tour (GT) road vehicle equipped with a series of active variable-geometry suspension (SAVGS) system using a PID, Fuzzy PID and LQR controller. Previous works have used mostly skyhook and PID controllers. In this paper, the choice of these three controllers to achieve two advantages are to be robust and optimal. The complex has been evaluated in several different ways, taking into account the specific road conditions. In the present study, unlike previous works, an attempt has been made to use a full-dynamic vehicle model. This choice will make the study more comprehensive and accurate than the dynamic behavior of the vehicle. This will be due to the simulation results approaching the actual test values. Basics of controller design are reducing vertical body acceleration and, more importantly, for lowering the vehicle roll angle and overall angular accelerations to increase vehicle roll stability. The main differences and innovations made in the control strategy, in addition to choosing type of the controllers, are emphasis on the resistance of the controllers and use of a combination of the control methods to achieve the desired result. To achieve these aims, modeling of the full vehicle's dynamic parameters along with considering the actual test conditions is highly required, which in the present work, most of the above are covered. In summary, this work, while improving the control purposes such as roll prevention over to the expected parameters of vehicle suspension, such as separating vibrations and ride comfort, reduces overall energy consumption by selecting type of the suspension used.
    Keywords: series active variable-geometry suspension; roll stability; Fuzzy-PID controller; linear quadratic regulator controller.

  • A Light-Duty Truck Model for the Analysis of On-center Handling Characteristics   Order a copy of this article
    by Yupeng Duan, Yunqing Zhang, Yan Wang, Jiongli Zeng, Peijun Xu 
    Abstract: For commercial vehicles, on-center handling characteristics deeply influences the driving safety and drivers feeling about the vehicle, since it represents steering feel and vehicle response on the highway. This research focuses on the on-center handling performance of light-duty trucks. A vehicle model was built to conduct the simulation of the on-center handling test. The model consists of a power steering system, non-independent front/rear suspensions, the powertrain system, and a mounted cab. Nonlinear properties of the power steering system, the friction hysteretic characteristic in the steering system, suspension system with leaf springs and tires are considered so as to reflect the complicated on-center handling characteristics. We conducted constant radius cornering tests, return-release tests, and high speed weave tests on a target vehicle. By comparing the test and simulation results, adjustments were made to the model parameters to improve simulation accuracy. A number of variables were altered to show its influence on the steering feel and vehicle response. The results show that the tires lateral force characteristics strongly affect the vehicle response. Steering gear ratio, steering system clearance, and caster angle strongly affect the steering feel.
    Keywords: Light-duty trucks; On-center handling; Dynamic model; Parameter sensitivity analysis.