Vehicle stability self-tuning control strategy based on joint criterion

2016 ◽  
pp. 490-498
Keyword(s):  
Control Strategy ◽  
Vehicle Stability ◽  
Self Tuning

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.

Vehicle Dynamics Control Based on Linear Quadratic Regulator

2009 ◽  
Vol 16-19 ◽  
pp. 876-880
Author(s):  
Si Qi Zhang ◽  
Tian Xia Zhang ◽  
Shu Wen Zhou
Keyword(s):  
Control Strategy ◽  
Vehicle Dynamics ◽  
Linear Quadratic Regulator ◽  
Active Safety ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Yaw Rate ◽  
Vehicle Dynamics Control ◽  
Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

A self-tuning load frequency control strategy for microgrids: Human brain emotional learning

2016 ◽  
Vol 75 ◽  
pp. 311-319 ◽  
Author(s):  
Mohammad Reza Khalghani ◽  
Mohammad Hassan Khooban ◽  
Esmaeil Mahboubi-Moghaddam ◽  
Navid Vafamand ◽  
Mohammad Goodarzi
Keyword(s):  
Human Brain ◽  
Control Strategy ◽  
Frequency Control ◽  
Emotional Learning ◽  
Load Frequency Control ◽  
Load Frequency ◽  
Self Tuning ◽  
Brain Emotional Learning

Performance comparison of electric-vehicle drivetrain architectures from a vehicle dynamics perspective

2019 ◽  
Vol 234 (4) ◽  
pp. 915-935
Author(s):  
Kerem Bayar
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Vehicle Dynamics ◽  
Tracking Control ◽  
Tracking Error ◽  
Vehicle Stability ◽  
Electric Motors ◽  
Sideslip Angle ◽  
Stopping Distance ◽  
Braking System

Recent electric vehicle studies in literature utilize electric motors within an anti-lock braking system, traction-control system, and/or vehicle-stability controller scheme. Electric motors are used as hub motors, on-board motors, or axle motors prior to the differential. This has led to the need for comparing these different drivetrain architectures with each other from a vehicle dynamics standpoint. With this background in place, using MATLAB simulations, these three drivetrain architectures are compared with each other in this study. In anti-lock braking system and vehicle-stability controller simulations, different control approaches are utilized to blend the electric motor torque with hydraulic brake torque; motor ABS, torque decomposition, and optimal slip-tracking control strategies. The results for the anti-lock braking system simulations can be summarized as follows: (1) Motor ABS strategy improves the stopping distance compared to the standard anti-lock braking system. (2) In case the motors are not solely capable of providing the required braking torque, torque decomposition strategy becomes a good solution. (3) Optimal slip-tracking control strategy improves the stopping distance remarkably compared to the standard anti-lock braking system, motor anti-lock braking system, and torque decomposition strategies for all architectures. The vehicle-stability controller simulation results can be summarized as follows: (1) higher affective wheel inertia of the on-board and hub motor architecture dictates a higher need of wheel torque in order to generate the tire force required for the desired yaw rate tracking. A higher level of torque causes a higher level of tire slip. (2) Optimal slip-tracking control strategy reduces the tire slip trends drastically and distributes the traction/braking action to each tire with the control-allocation algorithm specifying the reference slip values. This reduces reference tire slip-tracking error and reduces vehicle sideslip angle. (3) Tire slip trends are lower with the hub motor architecture, compared to the other architectures, due to more precise slip control.

Self-tuning Position Control for the Linear Long-stroke, Compound Switched Reluctance Conveyance Machine

2017 ◽  
Vol 8 (3) ◽  
pp. 1427
Author(s):  
J. F. Pan ◽  
Weiyu Wang ◽  
Zhang Bo ◽  
Norbert Cheung ◽  
Li Qiu
Keyword(s):  
Control Strategy ◽  
Position Control ◽  
The Self ◽  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Reluctance Machine ◽  
Self Tuning ◽  
Nonlinear Disturbance ◽  
Long Stroke ◽  
Linear Compound

This paper proposes a long-stroke linear switched reluctance machine (LSRM) with a primary and a secondary translator for industrial conveyance applications. The secondary one can translate according to the primary one so that linear compound motions can be achieved. Considering the fact that either one translator imposes a time-variant, nonlinear disturbance onto the other, the self-tuning position controllers are implemented for the compound machine and experimental results demonstrate that the absolute steady-state error values can fall into 0.03 mm and 0.05 mm for the secondary and primary translator, respectively. A composite absolute precision of less than 0.6 mm can be achieved under the proposed control strategy.

On Reverse Control Strategy and Anti-Wind Disturbance Analysis of Automotive EPS System

2010 ◽  
Vol 39 ◽  
pp. 529-534
Author(s):  
Jing Bo Zhao ◽  
Shao Yi Bei ◽  
Lan Chun Zhang
Keyword(s):  
Control Strategy ◽  
Lateral Displacement ◽  
Lateral Acceleration ◽  
Vehicle Stability ◽  
Wind Disturbance ◽  
Steering Control ◽  
Lateral Direction ◽  
Safety Improvement ◽  
Design Function ◽  
Steering Torque

Under the special situation of lateral wind disturbance, the lateral direction was resulted from the conventional obverse control strategy and influenced the vehicle stability. The 2-DOF full-vehicle model with the lateral wind disturbance and EPS dynamic model were designed. Reverse control strategy was designed where the EPS motor provided active steering control to prevent vehicle deflection with the input signal of steering torque under the lateral wind disturbance. In the EPS working process, the reverse control strategy and obverse control strategy were switched according to the drive situation to obtain the best vehicle stability. Anti-disturbance simulation was executed and the results shown that the yaw rate, the slideslip angle, the lateral acceleration and the lateral displacement have been weakened, and the vehicle stability is enhanced. The design of reverse control strategy has engineering significance to the overall design, function enhancement and optimization and steering manipulation and safety improvement.

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