Abstract
The range of electric vehicles (EV), especially those powered by aged battery packs, is partly limited by cell-to-cell imbalance, i.e., the weakest cell determines the performance of the entire battery pack. Active cell balancing can mitigate these differences, but balancing ad hoc discrepancies in voltage or state-of-charge (SoC) does not necessarily result in the best performance in terms of range. This brief employs a distributed feasibility approach to retrieve the maximum range and corresponding balancing currents for a specific scenario. Moreover, using aging data from literature and a real-time applicable model-predictive-controller, a lifetime projection is made on the benefits of active cell balancing, which shows that a significant extension of End-of-Life (EoL) is achieved, i.e., 10% for the considered example. Finally, we show when and why the applied balancing controller, which can effectively balance a battery pack using balancing currents with a maximum C-rate of only 1/50C, performs better than others in terms of maximizing the range.
Original language | English |
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Pages (from-to) | 2759-2766 |
Number of pages | 8 |
Journal | IEEE Transactions on Control Systems Technology |
Volume | 30 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Nov 2022 |
Keywords
- Active cell balancing
- Aging
- Batteries
- Load modeling
- Optimal control
- Optimization
- Predictive models
- Voltage
- electric vehicles (EV)
- lithium-ion batteries
- model-predictive control
- optimal control.
- optimal control