The sensor system of semi-active vehicle suspensions typically consists of four sprung accelerometers and four height sensors, making it expensive and complex to wire. To simplify and optimize the sensor arrangement, reduce the number and cost of body sensors, and enhance the vibration damping performance of vehicles, a new sensor arrangement scheme for magnetorheological (MR) suspensions is proposed. This scheme utilizes an Inertial Measurement Unit (IMU) mounted on the sprung mass and four relative displacement sensors. The complete formula for the acceleration signal on the four-way sprung mass is derived, with the correct reference system and angular rotation order selected to ensure the accuracy of the solution method. The Kalman filter is used to design the angular acceleration estimator. This approach considers the measurement noise inherent to the IMU and provides real-time feedback for the calculation. In the simulation, the IMU was positioned at the vehicle’s center of mass, and the estimated values from the IMU solution under various road excitations were compared to the actual sprung accelerations using the vehicle model. Additionally, the robust H∞ control algorithm was employed to regulate the magnetorheological dampers. By comparing the sprung accelerations at the vehicle’s center of mass under various road excitations, the accuracy of the calculation and the damping effectiveness of this magnetorheological suspension control system were confirmed.

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Body Attitude Control System for Magnetorheological Vehicle Suspension Based on IMU Solution

  • Xiaotao Yu,
  • Liyan Pan,
  • Shuaishuai Sun,
  • Jian Yang

摘要

The sensor system of semi-active vehicle suspensions typically consists of four sprung accelerometers and four height sensors, making it expensive and complex to wire. To simplify and optimize the sensor arrangement, reduce the number and cost of body sensors, and enhance the vibration damping performance of vehicles, a new sensor arrangement scheme for magnetorheological (MR) suspensions is proposed. This scheme utilizes an Inertial Measurement Unit (IMU) mounted on the sprung mass and four relative displacement sensors. The complete formula for the acceleration signal on the four-way sprung mass is derived, with the correct reference system and angular rotation order selected to ensure the accuracy of the solution method. The Kalman filter is used to design the angular acceleration estimator. This approach considers the measurement noise inherent to the IMU and provides real-time feedback for the calculation. In the simulation, the IMU was positioned at the vehicle’s center of mass, and the estimated values from the IMU solution under various road excitations were compared to the actual sprung accelerations using the vehicle model. Additionally, the robust H∞ control algorithm was employed to regulate the magnetorheological dampers. By comparing the sprung accelerations at the vehicle’s center of mass under various road excitations, the accuracy of the calculation and the damping effectiveness of this magnetorheological suspension control system were confirmed.