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The paper describes the idea of constructing the rapid development system of vehicle electric control subsystem in details by using hardware-in-the-loop (HiL) simulation technology for cost reduction in today's competitive business environment. This rapid development system is probably most effectively used in parallel with a new vehicle electronic control product. Once a desired simulation results are achieved, it can be verified by setting up the same configurations in the new product and comparing results. The feasibility of using such rapid development system is demonstrated through vehicle ABS algorithm development. Significant reduction of developing cycle time and cost has been achieved with the aid of this powerful tool and promising effectiveness of ABS algorithm has been validated in vehicle field test.

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, a new control strategy is proposed for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. The PID controller is used to minimize vehicle body vertical acceleration and the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to achieve optimal vehicle performances and adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, gain values and the membership function of fuzzy logic controller on-line.

Since the nonlinearity which inherently exists in vehicle system need to be considered in active suspension control law design, a new control strategy is proposed for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a PID controller and a fuzzy logic controller in two loops. In this paper, the investigation is mainly focused on vehicle ride comfort performance and simulations in straight running operating condition are presented. The control goal is to minimize vehicle body vertical and pitch accelerations for passenger comfort. The control system consists of two parallel control loops. One loop, using PID control, is to minimize vehicle body vertical acceleration; and the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors.

For a semi-active suspension design, an important subject is to determine the control law which can achieve good performance both in ride and handling performance. Because of its superiority in non-linear control systems and capability of learning on-line, the fuzzy neural networks (FNNs) control scheme is proposed in this paper for a semi-active suspension system with dynamic absorber. The quarter vehicle model is described by a nonlinear system with three DOF subject to irregular excitation from a road surface and FNNs control scheme is employed. The on-line learning of FNNs to optimize fuzzy inference system is presented. Four kinds of methods, including passive suspension respectively with and without dynamic absorber, semi-active suspension respectively using fuzzy control and FNNs control, are investigated by computer simulation and comparison is made.