scholarly journals Design of brake force distribution model for front-and-rear-motor-drive electric vehicle based on radial basis function

2018 ◽  
Vol 4 (48) ◽  
pp. 87-98 ◽  
Author(s):  
Binbin SUN ◽  
Tiezhu ZHANG ◽  
Song GAO ◽  
Wenqing GE ◽  
Bo LI
Keyword(s):  
Radial Basis Function ◽  
Electric Vehicle ◽  
Basis Function ◽  
Energy Recovery ◽  
Distribution Model ◽  
Motor Drive ◽  
Force Distribution ◽  
Multi Objective ◽  
Brake Force ◽  
Brake Force Distribution

To achieve high-efficiency and stable brake of a front-and-rear-motor-drive electric vehicle (FRMDEV) with parallel cooperative braking system, a multi-objective optimal model for brake force distribution is created based on radial basis function (RBF). First of all, the key factors, which are the coefficient of brake force distribution between the front and rear shafts, the coefficient of brake force distribution at wheels, the coefficient of regenerative brake force distribution between front and rear axles, that influence the brake stability and energy recovery of the FRMDEV are analyzed, the fitness functions of brake stability and energy recovery are established. Secondly, the maximum allowed regenerative brake torque influenced by the state of charge of battery is confirmed, the correction model of the optimal distribution coefficient of regenerative brake force is created according to motor temperatures. Thirdly, based on HALTON sequence method, a two-factor database, vehicle velocity and brake strength, that characterizes vehicle operation is designed. Then an off-line response database of the optimal brake force distribution is established with the use of particle swarm optimization (PSO). Furthermore, based on hybrid RBF, the function model of the factor database and the response database is established, and the accuracy of the model is analyzed. Specially, the correlation coefficient is 0.995 and the predictive error variance is within the range between 0.000155 and 0.00018. The both indicate that the multi-objective distribution model has high accuracy. Finally, a hardware-in-loop test platform is designed to verify the multi-objective optimal brake force distribution model. Test results show that the real-time performance of the model can meet the demand of engineering application. Meanwhile, it can achieve both the brake stability and energy recovery. In comparison with the original brake force distribution model based on the rule algorithm, the optimized one proposed in this paper is able to improve the energy, recovered into battery, by 14.75%.

Collaborative control of a dual electro-hydraulic regenerative brake system for a rear-wheel-drive electric vehicle

2018 ◽  
Vol 233 (4) ◽  
pp. 1035-1046 ◽  
Author(s):  
Jonathan Nadeau ◽  
Philippe Micheau ◽  
Maxime Boisvert
Keyword(s):  
Electric Vehicle ◽  
Energy Recovery ◽  
Rear Wheel ◽  
Brake System ◽  
Force Distribution ◽  
Hydraulic Brake ◽  
Brake Pressure ◽  
Wheel Drive ◽  
Brake Force ◽  
Brake Force Distribution

Within the field of electric vehicles, the cooperative control of a dual electro-hydraulic regenerative brake system using the foot brake pedal as the sole input of driver brake requests is a challenging control problem, especially when the electro-hydraulic brake system features on/off solenoid valves which are widely used in the automotive industry. This type of hydraulic actuator is hard to use to perform a fine brake pressure regulation. Thus, this paper focuses on the implementation of a novel controller design for a dual electro-hydraulic regenerative brake system featuring on/off solenoid valves which track an “ideal” brake force distribution. As an improvement to a standard brake force distribution, it can provide the reach of the maximum braking adherence and can improve the energy recovery of a rear-wheel-drive electric vehicle. This improvement in energy recovery is possible with the complete substitution of the rear hydraulic brake force with a regenerative brake force until the reach of the electric powertrain constraints. It is done by performing a proper brake pressure fine regulation through the proposed variable structure control of the on/off solenoid valves provided by the hydraulic platform of the vehicle stability system. Through road tests, the tracking feasibility of the proposed brake force distribution with the mechatronic system developed is validated.

scholarly journals Driving energy management of front-and-rear-motor-drive electric vehicle based on hybrid radial basis function

2019 ◽  
Vol 49 (1) ◽  
pp. 47-58
Author(s):  
Binbin Sun ◽  
Tiezhu Zhang ◽  
Wenqing Ge ◽  
Cao Tan ◽  
Song Gao
Keyword(s):  
Radial Basis Function ◽  
Predictive Model ◽  
Real Time ◽  
Electric Vehicle ◽  
Energy Management ◽  
Basis Function ◽  
Motor Drive ◽  
Torque Distribution ◽  
Loss Models ◽  
Motor Operation

This paper presents mathematical methods to develop a high-efficiency and real-time driving energy management for a front-and-rear-motor-drive electric vehicle (FRMDEV), which is equipped with an induction motor (IM) and a permanent magnet synchronous motor (PMSM). First of all, in order to develop motor-loss models for energy optimization, database of with three factors, which are speed, torque and temperature, was created to characterize motor operation based on HALTON sequence method. The response surface model of motor loss, as the function of the motor-operation database, was developed with the use of Gauss radial basis function (RBF). The accuracy of the motor-loss model was verified according to statistical analysis. Then, in order to create a two-factor energy management strategy, the modification models of the torque required by driver (Td) and the torque distribution coefficient (β) were constructed based on the state of charge (SOC) of battery and the motor temperature, respectively. According to the motor-loss models, the fitness function for optimization was designed, where the influence of the non-work on system consumption was analyzed and calculated. The optimal β was confirmed with the use of the off-line particle swarm optimization (PSO). Moreover, to achieve both high accuracy and real-time performance under random vehicle operation, the predictive model of the optimal β was developed based on the hybrid RBF. The modeling and predictive accuracies of the predictive model were analyzed and verified. Finally, a hardware-in-loop (HIL) test platform was developed and the predictive model was tested. Test results show that, the developed predictive model of β based on hybrid RBF can achieve both real-time and economic performances, which is applicable to engineering application. More importantly, in comparison with the original torque distribution based on rule algorithm, the torque distribution based on hybrid RBF is able to reduce driving energy consumption by 9.51% under urban cycle.

A Variable Proportional Valve Braking Force Distribution Strategy Including SOC Constraints of Electric Vehicles

2014 ◽  
Vol 597 ◽  
pp. 525-530
Author(s):  
Hong Xia Yu ◽  
Zhen Yang Lin
Keyword(s):  
Electric Vehicles ◽  
Energy Recovery ◽  
Distribution Area ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Proportional Valve ◽  
Brake Force ◽  
Distribution Line ◽  
Braking Force ◽  
Brake Force Distribution

Braking force distribution plays an important role in energy recovery of electric vehicles. A new braking force distribution based on the variable proportional valve is proposed to solve the traditional proportional valve braking force distribution problem. By considering the safety brake force distribution area, the variable proportional valve friction braking force distribution line is optimized, the regenerative braking force equations are deduced using the optimized friction braking force distribution line at different braking intensity, then the regenerative braking force is corrected by considering mechanical characteristics of motor and SOC of battery constraints. Simulation results show that the proposed regenerative braking energy recovery has been significantly improved.

scholarly journals Research on braking energy recovery strategy of electric vehicle based on ECE regulation and I curve

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987776 ◽  
Author(s):  
Shengqin Li ◽  
Bo Yu ◽  
Xinyuan Feng
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Battery State Of Charge ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

Electric vehicles can convert the kinetic energy of the vehicle into electric energy for recycling. A reasonable braking force distribution strategy is the key to ensure braking stability and the energy recovery rate. For an electric vehicle, based on the ECE regulation curve and ideal braking force distribution (I curve), the braking force distribution strategy of the front and rear axles is designed to study the braking energy recovery control strategy. The fuzzy control method is adopted while the charging power limit of the battery is considered to correct the regenerative braking torque of the motor, the ratio of the regenerative braking force of the motor to the front axle braking force is designed according to different braking strengths, then the braking force distribution and braking energy recovery control strategies for regenerative braking and friction braking are developed. The simulation model of combined vehicle and energy recovery control strategy is established by Simulink and Cruise software. The braking energy recovery control strategy of this article is verified under different braking conditions and New European Driving Cycle conditions. The results show that the control strategy proposed in this article meets the requirements of braking stability. Under the condition of initial state of charge of 75%, the variation of state of charge of braking control strategy in this article is reduced by 8.22%, and the state of charge of braking strategy based on I curve reduces by 9.12%. The braking force distribution curves of the front and rear axle are in line with the braking characteristics, can effectively recover the braking energy, and improve the battery state of charge. Taking the using range of 95%–5% of battery state of charge as calculation target, the cruising range of vehicle with braking control strategy of this article increases to 136.64 km, which showed that the braking control strategy in this article could increase the cruising range of the electric vehicle.

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