Abstract
Existing validation methods for equivalent circuit models (ECMs) do not capture the effects of operating lithium-ion cells over legislative drive cycles at low ambient temperatures. Unrealistic validation of an ECM may often lead to reduced accuracy in electric vehicle range estimation. In this study, current and power are used to illustrate the different approaches for validating ECMs when operating at low ambient temperatures (−15 °C to 25 °C). It was found that employing a current-based approach leads to under-testing of the performance of lithium-ion cells for various legislative drive cycles (NEDC; FTP75; US06; WLTP-3) compared to the actual vehicle. In terms of energy demands, this can be as much as ~21% for more aggressive drive cycles but even ~15% for more conservative drive cycles. In terms of peak power demands, this can range from ~27% for more conservative drive cycles to ~35% for more aggressive drive cycles. The research findings reported in this paper suggest that it is better to use a power-based approach (with dynamic voltage) rather than a current-based approach (with fixed voltage) to characterise and model the performance of lithium-ion cells for automotive applications, especially at low ambient temperatures. This evidence should help rationalize the approaches in a model-based design process leading to potential improvements in real-world applications for lithium-ion cells.
Highlights
Reduced driving range and battery performance at low ambient temperatures are a key market adoption barrier for battery electric vehicles (BEVs) [1]
The US06 was the most aggressive evidenced by the energy required per km at the cell level (1.81 Wh/km), the RMS power demand of the four legislative drive cycles considered as part of this study (Table 3)
The equivalent circuit models (ECMs) accuracy in output voltage estimation decreases for all the legislative drive cycles (Figure 10)
Summary
Reduced driving range and battery performance at low ambient temperatures are a key market adoption barrier for battery electric vehicles (BEVs) [1]. This limitation is primarily attributed to increased energy and power demands from on-board battery pack at low ambient temperatures [2,3]. This is further exacerbated by reduced accuracy in driving range estimation, which often contribute to an increased range anxiety amongst BEV users at such ambient temperatures [4,5].
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