基於人工智慧開發具主動控制與節能最佳化之電動車多元延距電能管理系統

The goal of this project is to develop a power management system (PMS) for hybrid electric vehicles. It is expected to improve the energy efficiency of green vehicles through the hybrid power design, power electronics, and artificial intelligence (AI), thereby extending battery life and increasing endurance. Afterward, electric vehicles can reach a level of commercialization. The project has completed the PMS with AI technology and developed its innovative active control and energy saving optimization strategy. The developed PMS was tested by standard driving cycle to evaluate its performance and endurance. The specific achievements of this project include: (1) Complete the design and implementation of the PMS for the fuel cell/lithium battery hybrid electric scooter (HES), (2) Complete the design and implementation of current sharing control (CSC) architecture for a parallel connected bidirectional DC-DC converters system, (3) Complete the active power split control (APSC) of the hybrid electric scooter, (4) Complete the optimal PSC design for the HES, (5) Complete the simulation and implementation of the CSC for the parallel connected bidirectional DC-DC converters system, and (6) Establish a platform and a real test scooter for experimentation. From the simulation and experimental results, it can be seen that the developed AI -based APSC and energy-saving optimization strategy can effectively improve the endurance of the HES. In this regard, the AI based PMS with APSC and energy saving optimization is effective for the HES.