This paper presents a hybrid algorithm combining fuzzy logic with equivalent consumption minimization strategy (ECMS) for energy management in parallel hybrid electric vehicles. The fuzzy control algorithm selects the mode of operation from 5 possible modes, i.e. electric motor (EM) only mode, internal combustion engine (ICE) only mode, EM + ICE mode, charging mode or regenerative mode. The solution provided by the fuzzy control algorithm is not optimal. Therefore, to obtain an optimal solution, the ECMS optimization method is applied when mode 3 (EM + ICE) and mode 4 (charging) are selected. The US06 or supplemental FTP driving schedule and the EPA highway fuel economy driving cycle have been used for highlighting the advantages of the proposed hybrid fuzzy + ECMS algorithm over the fuzzy-only and if-then-else rule-based control algorithms. Results attained reflect that the proposed hybrid fuzzy + ECMS improves fuel economy by around 27.6% in the case of US06 or supplemental FTP while it improves fuel economy by 16.3% in case of EPA highway fuel economy driving cycle. It is also shown that there is a minor increase in computational time and complexity in using this hybrid algorithm as compared to the other algorithms. The proposed hybrid fuzzy + ECMS algorithm does not require prior knowledge of the driving cycle, so it can be used for both online (when the driving conditions are unknown) and offline (when the entire driving cycle is known and predefined) strategies.
Parallel hybrid electric vehicles, fuzzy logic, equivalent consumption minimization strategy, optimization, fuel economy.
Vikas Gupta, Energy Management in Parallel Hybrid Electric Vehicles Combining Fuzzy Logic and Equivalent Consumption Minimization Algorithms, HCTL Open International Journal of Technology Innovations and Research, Volume 10, July 2014, ISSN: 2321-1814, ISBN: 978-1-62951-619-6.