Multi sensor fusion control technology for steering stability of hybrid electric vehicles
In order to meet the requirements of vehicle driving stability,the current steering control relies on a single sensor information,which is prone to ignoring many influencing factors,resulting in a relatively large side slip angle of the steering center of the vehicle after control.Therefore,hybrid electric vehicles have proposed multi sensor fusion control technology for steering stability.Consider the dynamic characteristics of hybrid electric vehicles during the steering process,construct a steering dynamics mod-el,and calculate the ideal yaw rate of the vehicle.Thoroughly analyze the impact of yaw rate and slip rate on vehicle steering stability,and obtain the expected yaw torque and slip rate adjustment torque.Consider the steering stability control problem of automobiles as a quadratic programming problem,com-bine BP neural network and conventional PID controller,design a steering stability control algorithm,and use the ideal,actual,and deviation values of vehicle steering parameters to calculate the stability control parameters.Finally,by integrating real-time information collected from multiple sensors,the steering attitude error of the vehicle is calculated and incorporated into the control structure,and the optimized control parameters are given.The experimental results show that after the application of the newly pro-posed control technology,the center of mass sideslip angle of the vehicle's steering does not exceed plus or minus 0.012 rad/s,meeting the steering driving requirements of hybrid electric vehicles.
hybrid electric vehiclesteering stabilitymultiple sensorsdata fusioncontrol technol-ogytarget identification
万方数据
维普
