Research On Active Suspension Control Strategy For Emergency Rescue Vehicles Based On Front Terrain Information

In recent years,natural disasters have occurred frequently in our country.As a kind of special rescue equipment to deal with unexpected accidents,emergency rescue vehicles need to ensure excellent driving mobility and ride comfort under various complex road conditions.Most of the traditional emergency rescue vehicles are equipped with passive suspension systems,whose structural parameters cannot be adjusted in real time according to the vehicle motion state and front terrain information,which leads to the limited vehicle driving performance on complex road conditions.The active suspension system can alleviate the impact of road surface by controlling the output force or torque of actuators,which effectively improve the vehicle’s driving mobility and ride comfort under complex terrain,and meet the performance requirements of emergency rescue vehicles for the suspension system.This paper relies on the National Key Research and Development Program(Project No.2016YFC0802902).In order to improve the driving mobility and ride comfort of emergency rescue vehicles,the vehicle front terrain construction technology and active suspension control method based on front terrain are systematically studied.The following are the main research works:(1)The vehicle positioning and front terrain constructing method based on the fusion of vehicle dynamics and multi-sensor information is studied.The improved error state Kalman filtering algorithm is used to achieve accurate evaluation of vehicle posture information.The 3D elevation map of front terrain is constructed by the Lidar sensor.Meanwhile,outlying and repeated points in the elevation map are solved through the statistical filter and gaussian fusion algorithm.Matlab simulation results indicate that the proposed positioning method effectively solves the problem of low positioning accuracy and poor stability of the vehicle location system.In addition,the proposed front terrain construction method can achieve the elimination of outlying points and fusion of repeated points in the elevation map.(2)The neural network model predictive control method based on vehicle front terrain is studied.Aiming at the nonlinear problems of the spring and damper in the active suspension system,the vehicle dynamics fitting model based on neural network algorithm is proposed.On this basis,A neural network model predictive control method based on front terrain is proposed.Considering the problem of parameter uncertainty and data fluctuation of sensors in hydraulic actuators,an adaptive control method based on first-order low-pass filter is proposed to realize the high-precision tracking control to desired force signals.Matlab simulation results show that,compared with the traditional PID and adaptive robust control,the control strategy for the hydraulic actuator proposed in this paper has higher tracking accuracy and better stability.In addition,compared with the passive suspension system and traditional model predictive controller,the neural network model predictive control strategy proposed in this paper has a better control effect on improving the ride comfort of rescue vehicles.(3)The event-triggered control method based on vehicle front terrain is studied.A Takagi-Sugeno fuzzy model is used to reduce the influence of time-varying load of rescue vehicles on the suspension control system.Aiming at the problems of data transmission delay between different sensors and controllers and network congestion caused by frequent data interaction in the suspension control process,an event-triggered control algorithm based on vehicle front terrain information is proposed.Meanwhile,A Lyapunov-Krasovskii function is introduced to prove the closed-loop stability of the event-triggered control system.Matlab simulation results show that,the proposed method solves the problems of data transmission delay and network congestion,and improves the ride comfort of vehicles.(4)The dynamic bessel planning control method based on vehicle front terrain is studied.The vehicle’s body information prediction method is proposed based on the vehicle dynamics and front terrain information.In order to improve the driving mobility,the vehicle posture trajectory is optimized through the high-order dynamic Bessel curve.Considering the nonlinearity,model uncertainty and unmeasurable state information of the hydraulic actuator,a model predictive control method based on the extended state observer is proposed to realize the dynamic tracking control of the hydraulic actuator to the displacement output signal.Matlab simulation results show that the proposed displacement control algorithm for the hydraulic actuator can achieve high-precision tracking control to displacement output signals.In addition,the proposed dynamic bessel planning control method is effective in improving the driving mobility.(5)The experimental platform of the emergency rescue vehicle is built,and the internal and external parameters of the integrated navigation system,lidar and accelerometer are calibrated.The proposed terrain construction technology and active suspension control strategy based on front terrain are tested under different road conditions.In the vehicle location and terrain construction experiment,the proposed vehicle location and terrain construction methods can achieve centimeter-level accuracy.In the suspension control experiment,the proposed neural network model predictive control strategy and event-triggered control strategy based on front terrain reduce the root mean square values of body’s acceleration,which effectively improve the ride comfort of the rescue vehicle.In addition,the proposed dynamic bessel planning control method based on front terrain reduces the root mean square values of body’s posture,which effectively improves the driving mobility of the rescue vehicle.