Date of Award
Doctor of Philosophy (PhD)
High voltage (HV) traction battery packs in electric-drive vehicles (HEV, PHEV, BEV) consist of a large number of battery cells connected in series. As individual cells exhibit mismatches in characteristics such as capacity, inner resistance, and run-time state-of-charge (SOC), cell balancing must be incorporated into the battery management system (BMS). Conventional passive cell balancing does not fully address the mismatch issues, which leads to shorter battery lifetime, and the need to over-size the battery pack. To overcome the problems associated with the conventional architecture, a modular battery management system incorporating both active cell balancing and high voltage (HV) to low-voltage (LV) dc-dc conversion has been developed. The HV-to-LV converter is a series-input, parallel-output dc-dc system with inputs connected across the battery cells or cell modules, while paralleled outputs supply loads on the LV bus. This thesis is focused on modeling, control and design of the modular battery management system. Several critical issues are addressed: (1) stability of the converter system with distributed control in energy storage application is analyzed and simulated; (2) the steady-state model of the dual-active-bridge (DAB) isolated converter with phase-shift modulation is refined and applied to the modular converter system with cell balancing; (3) practical methods for estimation of the lithium-ion battery state-of-charge (SOC) and state-of-health (SOH) are developed in forms suitable for implementation on low-cost microcontrollers. Finally, a modular hybrid balancing system with module-level active balancing and cell-level passive balancing is developed and experimentally validated. The techniques developed in this thesis can be applied to designs of large automotive battery packs with improved performance, reduced size, reduced cost, and longer lifetime.
Zhang, Fan, "Modeling and Control of a Modular Battery Management System for Lithium-ion Battery Packs" (2017). Electrical, Computer & Energy Engineering Graduate Theses & Dissertations. 153.