Electronic Stability Control Based on Motor Driving and Braking Torque Distribution for a Four In-Wheel Motor Drive Electric Vehicle

2016 ◽  
Vol 65 (6) ◽  
pp. 4726-4739 ◽  
Author(s):  
Li Zhai ◽  
Tianmin Sun ◽  
Jie Wang
Keyword(s):  
Electric Vehicle ◽  
Stability Control ◽  
Electronic Stability Control ◽  
Motor Drive ◽  
Torque Distribution ◽  
Braking Torque

scholarly journals Vehicle Stability Control Strategy Based on Recognition of Driver Turning Intention for Dual-Motor Drive Electric Vehicle

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Shu Wang ◽  
Xuan Zhao ◽  
Qiang Yu
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control ◽  
Motor Drive ◽  
Vehicle Stability ◽  
Lane Change ◽  
Vehicle Stability Control ◽  
Stability Control System ◽  
The Stability

Vehicle stability control should accurately interpret the driving intention and ensure that the actual state of the vehicle is as consistent as possible with the desired state. This paper proposes a vehicle stability control strategy, which is based on recognition of the driver’s turning intention, for a dual-motor drive electric vehicle. A hybrid model consisting of Gaussian mixture hidden Markov (GHMM) and Generalized Growing and Pruning RBF (GGAP-RBF) neural network is constructed to recognize the driver turning intention in real time. The turning urgency coefficient, which is computed on the basis of the recognition results, is used to establish a modified reference model for vehicle stability control. Then, the upper controller of the vehicle stability control system is constructed using the linear model predictive control theory. The minimum of the quadratic sum of the working load rate of the vehicle tire is taken as the optimization objective. The tire-road adhesion condition, performance of the motor and braking system, and state of the motor are taken as constraints. In addition, a lower controller is established for the vehicle stability control system, with the task of optimizing the allocation of additional yaw moment. Finally, vehicle tests were carried out by conducting double-lane change and single-lane change experiments on a platform for dual-motor drive electric vehicles by using the virtual controller of the A&D5435 hardware. The results show that the stability control system functions appropriately using this control strategy and effectively improves the stability of the vehicle.

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.

scholarly journals A Study on the Manufacture of Permanent Magnet Traction Control Valve for Electronic Stability Control in Electric Vehicles

2021 ◽  
Vol 11 (17) ◽  
pp. 7794
Author(s):  
Hak-Sun Lee ◽  
Sang-Gyun Park ◽  
Myoung-Pyo Hong ◽  
Han-Jin Lee ◽  
Young-Suk Kim
Keyword(s):  
Power Consumption ◽  
Permanent Magnet ◽  
Electric Vehicle ◽  
Fe Simulation ◽  
Control Valve ◽  
Stability Control ◽  
Continuous Heating ◽  
Electronic Stability Control ◽  
Traction Control ◽  
Magnetic Coil

Most solenoid valves in use today require a magnetic coil to be continuously energized to maintain the magnetization of the magnetic body in order to operate. The problem is that if the power is still supplied, the power consumption will continue. In addition, problems such as shortening the lifespan of solenoid valve internal parts due to the increase in the internal temperature of the electronic stability control (ESC) due to the continuous heating of the magnetic coil, and malfunction due to instantaneous power failure may occur. In this study, we conducted a study on the permanent magnet traction control valve (TCV) for ESC that can minimize the unnecessary power consumption of electric vehicle batteries. For optimal permanent magnet design, polarity direction setting and permanent magnet specifications were studied through FE simulation. A permanent magnet TCV was fabricated and an electromagnetic force test was conducted to compare and evaluate it with the FE simulation result. By using a permanent magnet, it was possible to lower the initial current value for the TCV to drive, therefore, it was possible to develop a permanent magnet TCV that can minimize the unnecessary power consumption of electric vehicle batteries.

scholarly journals Active torque distribution strategy for electric vehicle independent axle drive

2019 ◽  
Vol 100 ◽  
pp. 00037
Author(s):  
Artur Kopczyński
Keyword(s):  
Electric Vehicle ◽  
Electric Machines ◽  
Torque Distribution ◽  
Distribution Strategy ◽  
Braking Torque

Vehicles equipped with an electric independent axle drive have different properties compared to conventional vehicles. Distribution of driving or braking torque can be achieved by the proper control of the operation of electric machines without applying additional mechanisms. In this paper a method of active torque distribution between front and rear axles is presented. The method allows to use the maximum tyres adhesion and minimize slips. The results of simulation tests are presented, in which the active torque distribution with evenly torque distribution were compared.

STABILITY CONTROL STRATEGY FOR IN-WHEEL-MOTOR-DRIVE ELECTRIC VEHICLE BASED ON dSPACE

2020 ◽  
Vol 48 (2) ◽  
Author(s):  
Zhang Chuanwei ◽  
Zhang Dongsheng ◽  
Wang Rui ◽  
Zhang Rongbo ◽  
Wen Jianping
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control ◽  
Motor Drive
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