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Chinese Journal of Mechanical Engineering 2017年第4期30卷 982-990页

作者： You-Qun Zhao Hai-Qing Li Fen Lin Jian Wang Xue-Wu Ji College of Energy&Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Automotive Engineering Shandong Jiaotong UniversityJinan 250023China State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China

The accurate estimation of road friction coeffi- cient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coef- ficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coef- ficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode sur- face. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time andresist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.

关键词： road friction coefficient Real timeestimation External disturbance Different roadconditions

road friction coefficient Estimation by Using Lateral Dynamics Based on In-wheel Motor Driven Electric Vehicle

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Road Friction Coefficient Estimation by Using Lateral Dynami...

Approach to estimation of vehicle-road longitudinal friction coefficient

2015中国汽车工程学会年会

作者： Na Li Hui Chen Fan Xu School of Automotive Studies and Clean Energy Automotive Engineering Center Tongji University

By adopting a measurement noise adaptive Kalman filter and using the accurate information of driving torque provided by in-wheel motor driven electric vehicles,the tire longitudinal forces are ***,this paper puts forward a method to modify the original Dugoff tire model to expand the tire force working range as well as improve the ***,the joint estimation of road friction and vehicle sideslip angle is carried out based on a reduced-order extended Kalman filter with longitudinal forces as *** results show that the algorithm can accurately estimate road friction coefficient when vehicle is under lateral dynamics.

关键词： road friction coefficient longitudinal forces modified dugoff tire model sideslip angle extended Kalman filter

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Journal of Southeast University(English Edition) 2013年第3期29卷 310-315页

作者：宋翔李旭张为公陈伟徐启敏东南大学仪器科学与工程学院南京210096

According to the road adaptive requirements for the vehicle longitudinal safety assistant system an estimation method of the road longitudinal friction coefficient is *** method can simultaneously be applied to both the high and the low slip ratio conditions. Based on the simplified magic formula tire model the road longitudinal friction coefficient is preliminarily estimated by the recursive least squares *** estimated friction coefficient and the tires model parameters are considered as extended states. The extended Kalman filter algorithm is employed to filter out the noise and adaptively adjust the tire model parameters. Then the final road longitudinal friction coefficient is accurately and robustly estimated. The Carsim simulation results show that the proposed method is better than the conventional algorithm. The road longitudinal friction coefficient can be quickly and accurately estimated under both the high and the low slip ratio *** error is less than 0.1 and the response time is less than 2 s which meets the requirements of the vehicle longitudinal safety assistant system.

关键词： road friction coefficient recursive least squares extended Kalman filter vehicle longitudinal safety assistantsystem

Dual Extended Kalman Filter for Combined Estimation of Vehicle State and road friction

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Chinese Journal of Mechanical Engineering 2013年第2期26卷 313-324页

作者： ZONG Changfu HU Dan ZHENG Hongyu State Key Laboratory of Automotive Simulation and Control Jilin University

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.

关键词： vehicle state road friction coefficient estimation dual extended Kalman filter (DEKF)

road friction Estimation under Complicated Maneuver Conditions for Active Yaw Control

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Chinese Journal of Mechanical Engineering 2009年第4期22卷 514-520页

作者： LI Liang LI Hongzhi SONG Jian YANG Cai WU Hao The State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 China

road friction coefficient is a key factor for the stability control of the vehicle dynamics in the critical conditions. Obviously the vehicle dynamics stability control systems, including the anti-lock brake system（ABS）, the traction control system（TCS）, and the active yaw control（AYC） system, need the accurate tire and road friction information. However, the simplified method based on the linear tire and vehicle model could not obtain the accurate road friction coefficient for the complicated maneuver of the vehicle. Because the active braking control mode of AYC is different from that of ABS, the road friction coefficient cannot be estimated only with the dynamics states of the tire. With the related dynamics states measured by the sensors of AYC, a comprehensive strategy of the road friction estimation for the active yaw control is brought forward with the sensor fusion technique. Firstly, the variations of the dynamics characteristics of vehicle and tire, and the stability control mode in the steering process are considered, and then the proper road friction estimation methods are brought forward according to the vehicle maneuver process. In the steering maneuver without braking, the comprehensive road friction from the four wheels may be estimated based on the multi-sensor signal fusion method. The estimated values of the road friction reflect the road friction characteristic. When the active brake involved, the road friction coefficient of the braked wheel may be estimated based on the brake pressure and tire forces, the estimated values reflect the road friction between the braked wheel and the road. So the optimal control of the wheel slip rate may be obtained according to the road friction coefficient. The methods proposed in the paper are integrated into the real time controller of AYC, which is matched onto the test vehicle. The ground tests validate the accuracy of the proposed method under the complicated maneuver conditions.

关键词： active yaw control road friction coefficient estimation sensor fusion