Development of a Vehicle Stability Control System Using Brake-by-Wire Actuators

Author(s):  
Daegun Hong ◽  
Inyong Hwang ◽  
Paljoo Yoon ◽  
Kunsoo Huh

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional braking control systems. In order to achieve the superior braking performance through the wheel slip control, real-time information such as tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance, stability enhancement, etc. In this paper, a vehicle stability control system is developed based on the braking monitor, wheel slip controller, and optimal target slip assignment algorithm. The braking monitor estimates the tire braking force, lateral tire force, and brake disk-pad friction coefficient utilizing the extended Kalman filter. The wheel slip controller is designed based on the sliding mode control method. The target slip assignment algorithm is proposed to maintain the vehicle stability based on the direct yaw-moment controller and fuzzy logic. A hardware-in-the-loop simulator (HILS) is built including electrohydraulic brake hardware and vehicle dynamics software. The effectiveness of the proposed stability control system is demonstrated through the HILS experiment.

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.


2004 ◽  
Author(s):  
Masaru Nagao ◽  
Hikaru Watanabe ◽  
Eiichi Nakatani ◽  
Kouji Shirai ◽  
Kouji Aoyama ◽  
...  

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