Improving Accessible Capacity Tracking at Low Ambient Temperatures for Range Estimation of Battery Electric Vehicles

Tripathy, Yashraj; McGordon, Andrew; Barai, Anup · 2020 · Crossref

DOI: 10.3390/en13082021

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Summary

This study addresses the significant inaccuracy in range estimation for battery electric vehicles (BEVs) at low ambient temperatures, a critical issue exacerbated by the emerging electrification of aviation. The authors identify that traditional battery model parameterization experiments, conducted in air-based thermal chambers, fail to maintain isothermal conditions at sub-zero temperatures due to cell self-heating. This non-isothermal behavior leads to convoluted data where temperature and current effects are indistinguishable, resulting in models that overestimate usable capacity and driving range. The research aims to demonstrate that employing an immersed oil-cooled experimental setup to achieve near-isothermal conditions can significantly improve the accuracy of battery state estimation and, consequently, range prediction. The researchers utilized three 40 Ah lithium-ion pouch cells with Nickel-Manganese-Cobalt (NMC) cathodes and graphite anodes. They conducted galvanostatic discharge cycles at ambient temperatures of −20, −10, 0, and 25 °C across various C-rates (0.25C, 1C, and 3C) using two distinct thermal control methods: traditional forced-air convection in a thermal chamber and an active liquid cooling system using a low-viscosity silicone oil bath. The oil bath setup employed a chilling unit to maintain the coolant temperature, ensuring direct liquid cooling of the cell surfaces. To validate the impact of these parameterization methods on range estimation, the authors developed a first-order equivalent circuit model (ECM) with hysteresis. They simulated State-of-Charge (SOC) evolution and remaining driving range for a scaled US06 legislative drive cycle at −15, −5, and 5 °C, incorporating a 5 kW cabin heating load. The results revealed substantial discrepancies between the two thermal control methods. Under air cooling at −20 °C, cell self-heating caused significant temperature rises (up to 30.7 °C above ambient at 3C discharge), leading to artificially inflated capacity measurements. For instance, at 1C discharge, the air-cooled method yielded 31.7% higher capacity and 39.2% higher energy than the oil-cooled method. The oil-cooled setup maintained much lower surface temperature rises (e.g., 5.7 °C at 1C), providing data that accurately reflected the cell’s performance at the target ambient temperature. When these datasets were used to parameterize the ECM for range estimation, the oil-based approach reduced the estimation error from 49.3% to 11.7% at −15 °C. The air-based model significantly overestimated the remaining driving range because it failed to account for the severe capacity reduction inherent to true low-temperature operation. The significance of this work lies in its identification of experimental methodology as a root cause for poor range estimation accuracy in cold weather. By demonstrating that air-based thermal chambers produce non-isothermal data that misrepresents battery behavior at low temperatures, the paper provides a validated pathway for improving battery management systems. The adoption of immersed oil-cooled setups for parameterization allows for the creation of more accurate models, which is essential for mitigating range anxiety in BEVs and ensuring safety in electric aircraft applications where precise energy tracking is critical.

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