Design of Magnetorheological Damper Control System for Vehicle Suspension

Abstract

The damping force of Magnetorheological damper (MRD) can be controlled in a certain range by applying a steady magnetic field to reduce vehicle suspension vibration effectively. This paper presents the analysis of the damping characteristics of the twin-tube MRD, and the design of embedded control system for Twin-tube MRD used to semi-active vehicle suspension. The laws of varying damp force with current, displacement and frequency are investigated by testing for the damper, for instance the relationship curve of damping force vs. current. The control system is composed of controllable current driver and electrical control unit (ECU). ECU is developed based on MC9S12XDP512 chip. Signals that ECU acquired come from three types of sensor, i.e. digital temperature sensor, MEMS acceleration sensor and laser distance sensor embedded in MRD. The sampling frequency may exceed 400Hz. The programming is carried out in accordance with the state data acquisition and the improved On-Off control algorithm．Aiming at the high time response requirement of the MR damper, a Pulse-width modulation (PWM) current driver was designed. The hardware solutions drive circuit, interface circuit as wel1 as the software design of control system are discussed in detail. The proposed designed system has been put in actual MRD controlling application, whose test results prove its fast current response and high precision.

Automotive magnetorheological dampers: modelling and parameter identification using contrast-based fruit fly optimisation

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Design, modelling and testing of a novel high-torque magnetorheological damper

“…A novel rotary MR damper based on helical flow for increasing damping torque performance has been designed and tested by Yu [27]. Zhang Jinqiu [28][29][30] and Peng Zhizhao [31] optimized the rotary MR damper based on the conventional hydraulic damper and designed magnetorheological damper control system for vehicle suspension. The results show that the method is feasible, and the experiment results confirmed the good performance of the rotary MR damper.…”

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“…Backpropagation (BP) algorithm is a kind of neural computing algorithm, but its drawbacks have been made widespread, such as local minima, slow convergence, or dependent on initialized values in the training procedure and so on. To overcome the drawbacks of BP algorithm and some early algorithms, the new kinds of weight functions have been proposed in [2,3,4,5,6] for training neural networks, in which the weights are called weight functions, for example, the weights are cubic spline functions [3,4,5], B-spline weight functions [5], or improved B-spline weight functions [6] and so on. Although weight function theories and methods have been used in training neural networks in recent years and have many advantages, the trained weight functions are polynomials, which may be difficult for some rational problems.…”