Abstract
Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute(HSRI) tire model; the dual extended Kalman filter (DEKF) technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions(high-friction, low-friction, and joint-friction). On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.
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This project is supported by National Natural Science Foundation of China(Grant Nos. 51075176, 51105165)
ZONG Changfu, born in 1962, is currently a professor at State Key Laboratory of Automotive Simulation and Control, Jilin University, China. He received his PhD degree from Jilin University of Technology, China, in 1998. His research interests include automotive simulation and control.
HU Dan, born in 1984, is currently a PhD candidate at State Key Laboratory of Automotive Simulation and Control, Jilin University, China.
ZHENG Hongyu, born in 1980, is currently a lecture at State Key Laboratory of Automotive Simulation and Control, Jilin University, China. He received his PhD degree from Jilin University, China, in 2009. His research interests include automotive simulation and control.
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Zong, C., Hu, D. & Zheng, H. Dual extended Kalman filter for combined estimation of vehicle state and road friction. Chin. J. Mech. Eng. 26, 313–324 (2013). https://doi.org/10.3901/CJME.2013.02.313
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DOI: https://doi.org/10.3901/CJME.2013.02.313