Development of a hybrid energy storage sizing algorithm associated with the evaluation of power management in different driving cycles

In this paper, a hybrid energy storage sizing algorithm for electric vehicles is developed to achieve a semi-optimum cost-effective design. Using the developed algorithm, a driving cycle is divided into its micro-trips and the power and energy demands in each micro-trip are determined. The battery size is estimated because the battery fulfills the power demands. Moreover, the ultra-capacitor (UC) energy (or the number of UC modules) is assessed because the UC delivers the maximum energy demands of the different micro-trips of a driving cycle. Finally, a design factor, which shows the power of the hybrid energy storage control strategy, is utilized to evaluate the newly designed control strategies. Using the developed algorithm, energy-saving loss, driver satisfaction criteria, and battery life criteria are calculated using a feed-forward dynamic modeling software program and are utilized for comparison among different energy storage candidates. This procedure is applied to the hybrid energy storage sizing of a series hybrid electric city bus in Manhattan and to the Tehran driving cycle. Results show that a higher aggressive driving cycle (Manhattan) requires more expensive energy storage system and more sophisticated energy management strategy.