The stability control of electric vehicle based on optimal predictive control method

Author(s):  
Li Junwei ◽  
Cui Xiaolin
2021 ◽  
Vol 12 (1) ◽  
pp. 42
Author(s):  
Kun Yang ◽  
Danxiu Dong ◽  
Chao Ma ◽  
Zhaoxian Tian ◽  
Yile Chang ◽  
...  

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors.


Author(s):  
Yiwen Huang ◽  
Yan Chen

This paper presents a novel vehicle lateral stability control method based on an estimated lateral stability region on the phase plane of vehicle yaw rate and lateral speed, which is obtained through a local linearization method. Since the estimated stability region does not only describe vehicle local stability, but also define the oversteering and understeering characteristics, the proposed control method can achieve both local stability and vehicle handling stability. Considering the irregular geometric shape of the estimated stability region, a stability analysis algorithm is designed to determine the distance between vehicle states and stability region boundaries. State estimation or measurement errors are also incorporated in the distance calculation. Based on the calculated shortest distance between vehicle states and stability boundaries, a direct yaw moment controller is designed to maintain vehicle states stay within the stability region. CarSim® and Simulink® co-simulation is applied to verify the control design through a cornering maneuver. The simulation results show that the proposed control method can make the vehicle stay within the stability region successfully and thus always operate in a safe manner.


2014 ◽  
Vol 644-650 ◽  
pp. 313-316
Author(s):  
Wen Lai Liu

large-scale temperature stability control method is studied in this paper. In the process of large-scale temperature control, the stability of control is a very important indicator. To this end, this paper proposes a large-scale temperature stability control algorithm based on hierarchical control method. Balance equation of large-scale temperature stability control is created for the effective transmission of control data. According to the constant control theory, large-scale temperature stability control system design is achieved. Experimental results show that the proposed algorithm for large-scale temperature stability control system design, can greatly improve the stability of control, and get the satisfactory results.


2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Shu Wang ◽  
Xuan Zhao ◽  
Qiang Yu

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.


Author(s):  
Jiaxing Yu ◽  
Xiaofei Pei ◽  
Xuexun Guo ◽  
JianGuo Lin ◽  
Maolin Zhu

This paper proposes a framework for path tracking under additive disturbance when a vehicle travels at high speed or on low-friction road. A decoupling control strategy is adopted, which is made up of robust model predictive control and the stability control combining preview G-vectoring control and direct yaw moment control. A vehicle-road model is adopted for robust model predictive control, and a robust positively invariant set calculated online ensures state constraints in the presence of disturbances. Preview G-vectoring control in stability control generates deceleration and acceleration based on lateral jerk, later acceleration, and curvature at preview point when a vehicle travels through a cornering. Direct yaw moment control with additional activating conditions provides an external yaw moment to stabilize lateral motion and enhances tracking performance. A comparative analysis of stability performance of stability control is presented in simulations, and furthermore, many disturbances are considered, such as varying wind, road friction, and bounded state disturbances from motion planning and decision making. Simulation results show that the stability control combining preview G-vectoring control and direct yaw moment control with additional activating conditions not only guarantees lateral stability but also improves tracking performance, and robust model predictive control endows the overall control system with robustness.


2002 ◽  
Vol 68 (665) ◽  
pp. 102-107 ◽  
Author(s):  
Yasuaki KOHAMA ◽  
Hideo WATANABE ◽  
Satoshi KIKUCHI ◽  
Fukuo OHTA ◽  
Takayuki ITOH

2013 ◽  
Vol 644 ◽  
pp. 123-128
Author(s):  
Ling Yu Sun ◽  
Jian Hua Zhang ◽  
Xiao Jun Zhang

The wheel-legged mobile robot in a complex three-dimensional environment has strong through capacity .Study is very critical for the stability of the control of their body systems. In this paper , based on analysis of the structure of wheel-legged mobile robot designed, the stability is evaluated by the use of (Effective Mass Center) EMC , and the stability domain is established accordingly. A fuzzy adaptive PID control method is created , and verified by ADAMS and MATLAB co-simulation . Simulation results show that the robot in different terrestrial environment, can maintain good stability.


Engineering ◽  
2017 ◽  
Vol 09 (03) ◽  
pp. 338-350
Author(s):  
Bo Peng ◽  
Huanhuan Zhang ◽  
Peiteng Zhao

2018 ◽  
Vol 7 (2.12) ◽  
pp. 308
Author(s):  
Chang Hyun Kim ◽  
Houng Kun Joung

Background/Objectives: The power performance of electric vehicle chargers depends on the control efficiency of the power converters with on-board and off-board types. In this paper, a new control method is proposed for power converter of fast electric vehicle chargers in order to improve the power efficiency.Methods/Statistical analysis: The proposed control method is the optimal control to minimize the performance objectives from the predicted output, based on the system model. The discretized model of DC-DC converter with sampling time is derived by using lifting operation for taking into account with the desired prediction time.Findings: The existing conventional controllers are obtained by off-line optimal solution and applied to the systems. Once the control gain is determined, the controller is able to reflect the system response at the real-time.Improvements/Applications: The proposed control method has advantages to deal with system performances at real-time and the control actuation is updated every sampling time via the derived mathematical model. It can be directly applicable to real electric vehicle charger systems in industry.  


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