Reihaneh Ostadian

Hybridization of batteries with other energy storage systems looks like a promising solution for decreasing battery size and cost and extending its lifetime as well as electric vehicles' (EVs) driving range. This paper selected the Chevy Spark 2015 battery electric vehicle (BEV) integrating the ultracapacitor (UC) model as the investigated case study. Firstly, a dynamic model of the battery pack is developed in which its parameters, including the internal resistance, open-circuit voltage, and capacity, are adaptively updated based on the battery pack's instant temperature and state of charge (SOC). Then, two different energy management strategies (EMSs), i.e., a rule-based method and dynamic programming (DP), are implemented to allocate power between the energy sources. The EMSs are run over a standard driving cycle, and the hybrid energy storage system's (HESS's) outputs, including battery SOC, UC state of voltage (SOV), and the battery's capacity loss, are compared with the same vehicle equipped with the battery pack only. The simulation results show that DP can decrease SOC depletion by 4% and minimize the battery degradation by 39.2% on average compared to the proposed rule-based method for one of the standard driving cycles and three ambient temperatures.

By increasing the electrified vehicles trend, it is crucial to have a survey of what is done before and what is the open challenge for improving this industry. Powertrain electrification has heightened the need for an energy management strategy, which has been a continuing concern in the development of electrified vehicles. An energy management control unit manages power flow between different energy sources in an electrified powertrain that directly affects vehicle performance. There are inadequate numbers of studies on the most recent energy management strategies, which are compatible with real-world scenarios. Intelligent energy management strategies requirements are discussed in detail, and it is categorized to principle-based, data-driven, and composite-based methods. Besides, enabling technologies for implementing an energy management system with a comparison of different controller chips are described to give readers an experimental view. Future trends and existing challenges are presented, which generate fresh insight into energy management strategies.