Distributed Drive Electric Vehicle Longitudinal Velocity Estimation with Adaptive Kalman Filter: Theory and Experiment China Automotive Engineering Research Institute Company, Limited

Format:

Book

Conference/Event

Author/Creator:

Zhang, Zhang, author.

Contributor:

Leng, Bo

Xiong, Lu

Yu, Zhuoping

Zeng, Dequan

Conference Name:

WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2019

Summary:

AbstractVelocity is one of the most important inputs of active safety systems such as ABS, TCS, ESC, ACC, AEB and others In a distributed drive electric vehicle equipped with four in-wheel motors, velocity is hard to obtain due to all-wheel drive, especially in wheel slipping conditions. This paper focus on longitudinal velocity estimation of the distributed drive electric vehicle. Firstly, a basic longitudinal velocity estimation method is built based on a typical Kalman filter, where four wheel speeds obtained by wheel speed sensors constitute an observation variable and the longitudinal acceleration measured by an inertia moment unit is chosen as input variable. In simulations, the typical Kalman filter show good results when no wheel slips; when one or more wheels slip, the typical Kalman filter with constant covariance matrices does not work well. Therefore, a gain matrix adjusting Kalman filter which can detect the wheel slip and cope with that is proposed. Simulations are carried out in different conditions, including no wheel slips, one wheel slips, all wheel slip, passing a bump, and variable acceleration drive, and the results show that wheel slip has very little impact on estimation velocity. On-road experiments, including drive with sudden acceleration and deceleration, pass a bump, and accelerate on wet tile road, show satisfying results. On wet tile road, where the maximum slip rate is larger than 0.9, the velocity estimation error converges to within 5% in one second and to zero at last

Notes:

Vendor supplied data

Publisher Number:

2019-01-0439

Access Restriction:

Restricted for use by site license