An integrated battery unit regulation strategy - Gong, You (Cranfield University, 2023)
In the research community, hybrid battery systems (HBSs) employing dual battery chemistries have been proposed as a solution to address the suboptimal overall performance exhibited by most state-of-the-art single-chemistry battery systems used in electric vehicle (EV) ap- plications. Currently, the predominant approach for regulating power distribution among different battery chemistries in HBSs is to configure DC/DC converters. However, the cost and weight associated with this configuration pose a significant barrier to its practical application. To overcome these limitations, this project presents a novel HBS design that utilizes a discrete-switched structure combined with intelligent low-frequency switching algorithms to replace DC/DC converters. The discrete-switched structure offers a simpler system architecture and lower power electronics costs while still maintaining the power allocation functionality of DC/DC converters. The switching algorithms developed, en- compassing heuristic and model-predictive control algorithms, enable the switching of cells within battery strings based on battery status and power demands, facilitating effec- tive power management. Through simulations and experiments, the HBS equipped with intelligent algorithms effectively regulates power distribution among different batteries and ensures a broadly balanced state of charge. Moreover, the novel HBS configura- tion employing nickel cobalt manganese oxide (NCM) and lithium-sulfur (Li-S) batteries has been thoroughly investigated, encompassing the hardware structure and control algo- rithms. This design enables both a long-range capability and high-power performance in EV applications. It should be noted that this work assumed the usage of homogeneous cells and effective cell cooling. Future research endeavors will focus on exploring cell-to-cell variations and the development of corresponding thermal management systems.
Fotouhi, Abbas - Associate Supervisor
Keywords: Batteries; Modeling; Control algorithm; Topology; Costs; Switches; Resource management