Bacterial foraging algorithm for the optimum on-line energy management of a three-power-source hybrid powertrain

This research aims for developing an online energy management optimisation for a three-power-source hybrid powertrain based on Bacterial Foraging Approach (BFA) for environmental protection. The hybrid vehicle dynamics was constructed by modelling control-oriented subsystems on the Matlab/Simulink platform. For rule-based control as the baseline case, five operation modes were used. For the BFA, it was established for searching two control outputs for three power sources: the power split ratios with three given inputs: rotational speed, required power, and battery state-of-charge (SOC). The main procedures for optimal solutions were: (1) chemotaxis; (2) reproduction, and (3) elimination-dispersal. Ten bacteria were selected for the 2-dimensional optimum search according to the cost function with physical constraints: the equivalent fuel consumption. To evaluate the 'degree of optimisation', the Equivalent Consumption Minimisation Strategy (ECMS) was employed. Control laws were integrated into the hybrid powertrains with two test scenario: FTP-72 and NEDC driving cycles. The equivalent fuel reduction percentages compared to the rule-based control for BFA and ECMS are 19.8 and 33.3% for FTP72, while 43.6 and 46.1% for NEDC. The degree of optimisation for FTP and NEDC are 84.2 and 95.5%, respectively. It proves that the BFA was suitable for hybrid energy management. Real vehicle verification will be conducted in the future for environmental protection.