Novel Degradation Model-Based Current Derating Strategy for Lithium-Ion-Batteries

Abstract

Derating is the operation of an electrical or electronic device at less than its rated maximum capability in order to ensure safety, extend lifetime or avoid system shutdown. Relatively simple derating approaches have been proven effective for lithium-ion batteries. They are typically based on limiting battery charging and discharging currents to prevent operation outside certain operating areas, which are bounded by state-of-charge (SOC), voltage, or temperature levels, taken individually. The manufacturer’s datasheet provides hard limits for these operating areas, defining the so-called safe operating area (SOA). In order to prolong battery lifetime, more restrictive limits than the SOA can be defined, but this leads to reducing battery performance more frequently and intensively. However, it should be noted that these simple derating approaches do not fully capture the complexity of battery degradation mechanisms, since the actual rate of degradation is the result of an interaction of multiple operating conditions. Thus, they may overestimate or underestimate the optimal current limit. Indeed, many advanced degradation models that consider a combination of operating conditions have been proposed in the literature to predict the rate of degradation, in terms of capacity loss and/or internal resistance increase.With this in mind, we propose the integration of an advanced degradation model in the derating strategy and thereby reduce degradation without significant losses in performance. The degradation model calculates the maximum battery current that will ensure reduced degradation rates, both for calendar and cycle related ageing processes. The calendar ageing rate is limited by defining the SOC-dependent maximum temperature that will keep the rate below a certain level, and then limiting the current accordingly, aiming to reduce self-heating effects that lead to temperature rise. The cycle ageing rate is limited by calculating the SOC and temperature-dependent maximum current that will keep the rate below a certain level, and then controlling the current accordingly. The advanced degradation model and the control strategy are parameterized for a lithium iron phosphate/graphite cell.The algorithm is evaluated in simulations for a low-cost battery energy storage system (BESS) with passive thermal management. The BESS is installed outdoors and used as a buffer in a stationary residential photovoltaic application in Berlin, Germany. Two scenarios are used as a benchmark: 1) no derating; and 2) simple SOA-based current derating. In comparison, this novel approach achieves a large increase of 59 % in energy throughput over its lifetime, while system performance is only slightly reduced by 9 % through derating.Hence, we conclude that, in the case of low-cost BESS with passive thermal management, this novel degradation-aware derating strategy enables significant extension in lifetime operation with negligible impact on battery performance.Future work could evaluate the impact of the technology on BESS with active management approaches, such as active thermal management, hybridization, advanced balancing systems or by-passing. Acknowledgements This work was kindly supported by the EPSRC Faraday Institution Multi-Scale Modelling Project (EP/S003053/1, grant number FIRG003). References (1) Schimpe, M., von Kuepach, M. E., Naumann, M., Hesse, H. C., Smith, K., & Jossen, A. (2018). Comprehensive modelling of temperature-dependent degradation mechanisms in lithium iron phosphate batteries. Journal of The Electrochemical Society, 165(2), A181.(2) Schimpe, M., Naumann, M., Truong, N., Hesse, H. C., Santhanagopalan, S., Saxon, A., & Jossen, A. (2018). Energy efficiency evaluation of a stationary lithium-ion battery container storage system via electro-thermal modeling and detailed component analysis. Applied Energy, 210, 211-229.(3) Barreras, J. V., Raj, T., & Howey, D. A. (2018, October). Derating Strategies for Lithium-Ion Batteries in Electric Vehicles. In IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society (pp. 4956-4961). IEEE. Figure 1