Compensation approach for discretization constraint in automobile powertrain control and its performance evaluation

Abstract

In this paper, we propose a vibration suppression method that takes fuel cutoff into account for an automobile powertrain during rapid acceleration and investigate its effectiveness. An automobile powertrain transmits engine torque to the tires, which causes vibration of the vehicle body during rapid acceleration. The engine is used as an actuator to control this vibration. However, the engine output has a constraint by fuel cut. This degrades the vibration suppression effect of vibration control. In addition, all vehicles will be controlled via controller area networks. The discretization width of control signals and the communications traffic are in the relationship of trade-off. The communications traffic in vehicles will increase in the future. Therefore, we need a control system that can suppress vibration even with coarse discretization widths. In this study, we propose a powertrain vibration control method using an optimal dynamic quantizer as the countermeasure. Optimal dynamic quantizer minimizes the effects on the tracking error (in the control system) due to the quantization. Then, we quantitatively examine the robustness at various quantization widths for the proposed control system. As a result, the optimal dynamic quantizer allows for smoother acceleration while suppressing vibration compared to the case with static quantizers. In conclusion, the performance of the proposed control system is investigated quantitatively.

Keywords

• automobile powertrain
• vibration control
• functional model
• model-based controler
• fuel cut
• optimal dynamic quantizer
• nonlinearity