418645 Quantifying EV Battery Lifespan and Its Impact on Battery Warranty Strategy through a Battery Aging Model and a Micro-Level Transportation Network

Monday, November 9, 2015: 6:30 PM
Exhibit Hall 1 (Salt Palace Convention Center)
Xiaohui Liu1, Shubham Agrawal2, Xing Jin3, Ashish Vora3, Srinivas Peeta2, Gregory Shaver3 and Joseph Pekny1, (1)Chemical Engineering, Purdue University, West Lafayette, IN, (2)Department of Civil Engineering, Purdue University, West Lafayette, IN, (3)School of Mechanical Engineering, Purdue University, West Lafayette, IN

The transportation sector accounts for about 70% of the total oil consumptions in the US. Conventional vehicles normally use fossil fuels as their energy sources. The depletion of fossil fuels and the threat of climate changes promote the development of transportation electrification. Several commercialized Electric Vehicles (EV) have already entered the market for a few years.  However, greater deployment of EVs still faces several challenges. The concern of useful lifetime of EV batteries due to degradation is one of them. Lifespan information of populations of EV batteries is still scarce. Therefore, understanding the lifespan characteristics of EV batteries is significant for EV adoption, vehicle resale, and battery warranty strategy design. 

This study quantifies how different Electric Vehicle usage patterns affect EV battery lifespans. Real world household vehicle travel information is extracted from the National Household Travel Survey (NHTS) database. A micro-level transportation model based on the Indianapolis network is built to generate realistic drive cycle data. Then whole household vehicle usage pattern information is obtained by matching the travel information with drive cycles. A physical EV energy consumption model is used to simulate the battery state-of-charge (SOC) and power profiles. With this detailed battery power data, a battery aging model derived from the literature is used to predict battery lifespan for a simulated population of vehicle usage patterns. In order to understand the effect of charging behavior on battery lifespan, two charging scenarios are examined: only charging at home, charging at home and work.

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