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Due to the expense and time commitment associated with extensive product testing, vehicle manufacturers are developing new simulation techniques to verify vehicle component performance with less testing and more confidence in the final product. Battery lifetime is of particular difficulty to predict, since each battery is different and there are many different control scenarios that could be implemented based on the specific requirements of each battery type. In order to solve this problem for a 12V auxiliary lead-acid battery, a battery durability analysis model has been previously adapted from lithium-ion applications, which is capable of verifying the impact of lead-acid battery durability in a short period of time. In this study, calibration tools for this model were developed and are presented here, and durability analysis and verification are performed for the application of new electric vehicles.

Premature failure in lead-acid batteries used in starting, lighting, and ignition applications has led to warranty issues which can be resolved by predicting the contributing factors of battery aging and evaluating different design alternatives. Battery degradation in real vehicles is accelerated by dark currents from an integrated dashboard camera which are drawn while the ignition is turned off, high ambient temperatures, a shortage of the battery charge rate, and the intermittent occurrence of bad starts during idle-stop-and-go operation. Existing battery durability verification requires a long period of more than 4 months using experimental deep discharge testing and does not reflect the various actual vehicle driving conditions of the customer. In order to improve this, the present work aims to develop a battery aging prediction model that reflects the various operating conditions of actual vehicle driving patterns.