Vision based Multi-rate Estimation and Control of Body Slip Angle for Electric Vehicles

Among many vehicle states, body slip angle is one of the most important information for vehicle motion control. Due to the high costs to measure body slip angle with specific devices, it is necessary to investigate estimation methods using existing cheap sensors. From the viewpoint of sensor configuration, gyroscope, steering angle sensor, etc. are often employed for body slip angle estimation; in this research, two pieces of information provided by vision system are also utilized as additional measurements. Nevertheless, the sampling rate of normal camera is much slower compared to the other kinds of on board sensors; for electric vehicles (EVs), motors' control period is shorter than the sampling time of cameras, which also brings multi-rate issue. Moreover, the time delay caused by image processing is usually too long to be neglected. In this paper, single-rate and multi-rate Kalman filters considering measurement delay are designed for body slip angle estimation, and a body slip angle controller is designed with the estimated result as feedback. First of all, vehicle model and visual model as well as the multi-rate and delay issues are explained; then, single-rate and multi-rate Kalman filters are designed for body slip angle estimation; and then, body slip angle controllers with single-rate and multi-rate estimators are compared followed with simulations and experimental results; finally, conclusion and future works are presented.