Research On Vehicle Position And Attitude Control Method Based On GPS/IMU Data Fusion

Compared with transmission passive suspension and semi-active suspension,active suspension has better body attitude control performance,and is superior in improving vehicle ride comfort and handling stability.Among many types of vehicles,emergency rescue vehicles require higher performance of active suspension because of their special use,complex working environment and comprehensive consideration of vehicle-mounted precision rescue equipment and casualty protection.Based on the national key R&D project "Research on Key Technologies of Chassis and suspension for high-mobility emergency rescue vehicles(including fire-fighting vehicles)"(project number: 2016FYC0802902),this paper explores the optimization of active suspension and its control strategy,thereby improving the ride comfort and handling stability of rescue vehicles.In recent years,active suspension,multi-equipped with accelerometers,displacement sensors and other sensing devices,these devices under the interference of complex environment and noise,the measured values are not accurate,and too many sensing devices easily cause data error superposition,affecting the follow-up active control and optimization work.In this paper,GPS and IMU inertial measurement units are used to extract the body centroid pose information,and Kalman filter algorithm is used to fuse and optimize the data to obtain accurate body pose data.The three-axis vehicle dynamics model is established,and the decentralized control idea is introduced.The centroid pose is decoupled to the six single-cylinder actuators of the rescue vehicle.The fuzzy adaptive PID control strategy is used to realize the suspension actuator control.Built the suspension evaluation,through MATLAB-AMESim co-simulation platform to build,compared with passive suspension,verify the validity of the Kalman filter GPS and inertial navigation system based on the idea of integration of body posture test data.Simulation and experimental results show that the designed Kalman filter fusion algorithm can keep the error in a low range;the vehicle attitude adjustment scheme based on Kalman filter GPS and IMU fusion data is in the body acceleration,pitch acceleration,roll angle In terms of acceleration and suspension travel,the rms value is reduced by 34.72%?24.76%?27.57% and 27.57%,respectively,compared with the passive suspension under the same experimental conditions.This paper takes three-axle heavy-duty emergency rescue vehicle as the optimization object.,and based on Kalman filter GPS/IMU data fusion,the train of thought of auto-body posture extraction and attitude decentralized control strategy has certain application value and practice significance.It provides a good foundation for the optimization strategy and decoupling strategy of data fusion based on vehicle attitude measurement.