Integrated Optimal Energy Management/Gear Shifting Strategy Using Bacterial Foraging Algorithm for a Three-Power-Source Hybrid Powertrain

• Main Authors: Shih, Po-Lin, 施伯霖
• Other Authors: Hung, Yi-Hsuan
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/wdaw58

碩士 === 國立臺灣師範大學 === 工業教育學系 === 105 === The purpose of this study is to develop the bacterial foraging algorithm (BFA) by applying it to the energy management/gear shifting strategy system of a three-power-source hybrid powertrain. Furthermore, this study was practical in nature, as it used the real-time simulation Hardware-in-the-Loop (HIL) to verify the algorithm’s feasibility. This study employs HIL to assess the influence that using BFA will have on the energy management and gear shifting strategy control of a three-power-source hybrid powertrain. The vehicle weighs 1,368 kilograms and its subsystems include a 43kW internal combustion engine, 30kW motor, 15kW integrated starter generator, and a 1.872kW-h Ah lithium battery. There are three primary steps for the energy management system and BFA energy management control: 1) chemotaxis, 2) reproduction, and 3) elimination-dispersal. The overall number of iterations was 30, and 80 bacteria were used carry out optimal energy management. BFA and two control strategies were used to carry out a comparison of fuel consumption with the NEDC (New European Driving Cycle) driving pattern. 1) Rule-based management: There are five control modes, which are system preparation, battery charging mode, electric mode, hybrid power mode, and extended range mode; the engineer used his experience to determine when to set and change modes. 2) Equivalent consumption minimization strategy (ECMS): By incorporating the global search algorithm (GSA), we searched for all the scope’s possibilities in order to find the most minimal fuel consumption for power distribution ratio and gear shifting strategy. At the end of the study, we used HIL to simulate the feasibility and verify fuel consumption benefits of BFA on vehicle control units (VCU) in real time. A basic rule base, ECMS, BFA, and real-time were the four conditions for the equivalent consumption with the NEDC driving pattern: 538.9g, 209.6g, 248.9g, and 253.6g were their respective values. The equivalent consumption values with a FTP-72 driving cycle were 579.2g, 291g, 316.3g, and 320.38g. ECMS, BFA, and real-time were compared with a basic rule base when using a NEDC driving pattern to determine percentage values for improvement in energy consumption: 61%, 53.8%, and 52.9%. Percentage values for improvement in energy consumption for a FTP-72 driving cycle were 49.7%, 45.3%, and 44.6%. The improvement in equivalent consumption values for BFA and real-time for the NEDC driving pattern and FTP-72 driving cycle were 98% similar, and they were only outperformed by ECMS, which was the optimal solution. In the future, this experiment will be used to test a three-power-source e-CVT hybrid-powered vehicle.