Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles

TL;DR

This paper models EV battery aging to optimize bidirectional charging, revealing significant cost impacts and guiding sustainable smart charging strategies for electric mobility and grid support.

Contribution

It introduces a concise battery aging model integrated into a realistic smart charging scenario, highlighting the importance of thermal effects and economic considerations.

Findings

Battery aging costs can increase operating expenses by about 30%.

Thermal modeling is crucial for charging above 7 kW.

V2G profitability depends on aging costs and electricity price spread.

Abstract

Smart charging of Electric Vehicles (EVs) reduces operating costs, allows more sustainable battery usage, and promotes the rise of electric mobility. In addition, bidirectional charging and improved connectivity enables efficient power grid support. Today, however, uncoordinated charging, e.g. governed by users' habits, is still the norm. Thus, the impact of upcoming smart charging applications is mostly unexplored. We aim to estimate the expenses inherent with smart charging, e.g. battery aging costs, and give suggestions for further research. Using typical on-board sensor data we concisely model and validate an EV battery. We then integrate the battery model into a realistic smart charging use case and compare it with measurements of real EV charging. The results show that i) the temperature dependence of battery aging requires precise thermal models for charging power greater than 7 kW, ii) disregarding battery aging underestimates EVs' operating costs by approx. 30%, and iii) the profitability of Vehicle-to-Grid (V2G) services based on bidirectional power flow, e.g. energy arbitrage, depends on battery aging costs and the electricity price spread.