Reliability-Oriented Configuration Optimization of More Electrical Control Systems

More electrical vehicles adopt dissimilar redundant control systems with dissimilar power supplies and dissimilar actuators to achieve high reliability and safety, but this introduces more intricacy into the configuration design. Currently, it is difficult to identify the optimum configuration via the conventional trial-and-error approach within an acceptable timeframe. Hence, it is imperative to discover novel methods for the configuration design of more electrical vehicles. This paper introduced the design specification of more electric vehicles and investigated the contribution of different kinds of actuators, presenting a new multi-objective configuration optimization approach on the foundation of system reliability, weight, power, and cost. By adopting the non-dominated sorting genetic algorithm-II (NSGA-II), the Pareto optimization design set was obtained. Then, the analytic hierarchy process (AHP) was introduced to make a comprehensive decision on the schemes in the Pareto set and determine the optimal system configuration. Eventually, numerical results indicated that the reliability of our designed configuration increased by 5.89% and 55.34%, respectively, compared with dual redundancies and single redundancy configurations, which verified the effectiveness and practicability of the proposed method.