Online Energy Management of City Cars with Multi-Objective Linear Parameter-Varying L2-Gain Control

Abstract

Abstract:This work aims at online regulating transient current out of the batteries of small-sized electric cars that transport people and goods around cities. In a city with heavy traffic, transient current dominates the energy economy and propulsion capability, which are in opposition to each other. In order to manage the trade-off between energy consumption per distance and propulsion capability in transience, the authors improve on previous work on multi-objective linear parameter-varying (LPV) L2-gain control. The observer embedded into this multi-objective controller no longer assumes Kalman-filtering structure, and structural conservatism is thus removed. A full-spectrum set of experiments is performed. The results reveal that the feedback design significantly improves energy-motion management.

Stability Driven Optimal Controller Design for High Quality Images

“…Several sufficient conditions on stability and robust stability for sampled-data systems and the uncertain sampled-data systems, respectively, have been provided in terms of LMI. In an urban environment with heavy traffic, the transient current of battery of the small-sized electric car is controlled by multi-objective L2-gain, which is formulated by LMI [24]. In wind generation systems, the stability problems were reduced to a linear matrix inequality (LMI) problem and the current controller was also designed by the LMI method [25].…”