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The performances of some vehicle control systems are influenced by changes in the weight of the vehicle. In these systems, it is important to be able to estimate the weight without the need for special sensors. When we use physical models to do this, we have to provide estimates for two or more unknown parameters. In addition, since such a method is influenced by disturbances in the measured signals, it is difficult to maintain an acceptable level of accuracy. So, after analyzing the physical phenomena, we developed a new method that eliminates the influence of the disturbances from the measured signals and constructed an estimation system that has a minimum number of unknown parameters that was capable of providing a more accurate estimate of a vehicle weight. This method was applied to the braking force control of an automatic transmission and its efficacy was verified.

In order to increase the transfer efficiency in a metal V-belt type CVT (Continuously Variable Transmission), it is effective to lower belt clamping force from a current setting value. However, setting the clamping force too low will cause a macro slip (large belt slip). Thus, in order to set the clamping force to the proper level, the friction characteristics between the belt and the pulley (belt friction characteristics) must be understood in detail, and the macro slip threshold must be defined. In this paper, we shall propose a friction expression model for a metal V-belt type CVT and use this model to explain the speed reducing ratio dependence and speed dependence of the maximum friction coefficient (μmax). We shall also define the macro slip threshold in torque fluctuation environment.

The torque converter clutch slip control system adopted in the Toyota A541E automatic transaxle engages the torque converter clutch by applying a steady slip speed to prevent the torque fluctuation of the engine to be transmitted to the drivetrain while enhancing the transmission efficiency of the torque converter. The feedback controller of the slip speed adopts the H∞ (H-Infinity) control theory which offers a high level of robust stability, and is the first of its kind in a mass produced component. As a result, a highly accurate and reliable system has been realized, contributing to large-scale fuel economy.

This paper presents a new method for estimating the ambiguous change in a 4WS control system using a failure detection filter. This filter is designed to discriminate ambiguous failure modes in the control system by processing output errors between sensors and an observer. The result of the experiments using a 4WS vehicle revealed that the filter can estimate the failures of the sensors and the actuator with high accuracy. The effects of a lateral wind and other disturbances on the filter were also clarified.

Self-Tuning Regulators, based on both Minimum Variance Control theory and Recursive Extended Least Squares method, are applied to fuel injection/spark ignited automotive engines in order to improve idle speed stability. Simplified mathematical models, with consideration for stochastic combustion variation, are used to describe idle speed dynamics. Model parameters and control gains are calculated in every combustion cycle by using a 16-bit microcomputer. Fuel injection rate and alternator load manipulation are independently examined as control forces. It is founded that (1) these techniques for cotrolling fuel injection rate and alternator load provide over 10% and 30% reduction of engine speed fluctuation, respectively, in comparison with the conventional control systems and (2) this system, in which the control gains are tuned to the appropriate levels, can operate stably in sudden changes of air flow rate and external load.