Multi-objective tradeoff optimization of predictive adaptive cruising control for autonomous electric buses: A cyber-physical-energy system approach

Recently, Cyber-Physical System (CPS) has served as a cutting-edge technology for next-generation industrial applications, and is developing rapidly and inspires many application domains. The autonomous electric bus (AEB) that integrates the communication, perception, and control within vehicle dynamics is a typical CPS. However, the energy management is ignored in the vehicle cyber-physical system. Thus, a novelty cyber-physical-energy system (CPES) approach with deep integration and interaction of the cyber system with physical system for the energy management used cruising control is imposed. Under the new CPES framework, the energy consumption and battery capacity degradation are optimized in different driving environment. Simulation results show that the tradeoff optimization control algorithm can keep battery health by optimizing motor operating mode with a slightly penalty on the energy consumption. The total system cost effective analysis shows that the battery service lifetime is improved by about 41.59% with the proposed method, and even with the slightly sacrifice of power consumption, the whole vehicle economy is improved by about 10.08%, compared with the strategy optimizing the power consumption only. Additionally, the equivalent driving distance is significantly extended up to 70.87% when compared to the case that only energy consumption is optimized. Besides, the AEB with CPES framework not only keeps the host vehicle within the safe distance with the preceding vehicle, but optimizes the motion planning as well. The results validate the feasibility and effectiveness of the CPES-based optimization framework, and demonstrate the advantages of the tradeoff optimization energy management strategy.