Fast charging technology of lithium-ion batteries is critical to commercial application of electrical vehicles (EV). Typically, recharging lithium-ion batteries using standard charging methods takes more than one hour which is considerably longer than refueling of the internal-combustion-engine (ICE) car, roughly 8-10 min. To reduce the charging time, fast charging increases the total current which can adversely affect the cycle life, performance and safety of the battery, such as lithium plating, increased battery temperature, higher heat generation rate, and thermal runaway. The charging energy efficiency can be reduced because of the increased heat generation during fast charging. Therefore, controlling the temperature rise and improving the charging energy efficiency using well-designed fast charging strategies are indispensable for its application in electric vehicles.

The objective of this work is to optimize the charging current profile based on electrochemical thermal model and dynamic programming for a 26650 cylindrical lithium iron phosphate (LFP) battery. The proposed model is implemented on a multi-stage constant current (MSCC) fast charging strategy for charging from 0 % to 80 % of its rated capacity within 30 minutes. The goal of the optimization is to maximize the charging energy efficiency or/and minimize the temperature rise and charging voltage. The control variable of various charging current protocols using the C-rate level ranging from 0.6 C-rate and 2.6 C-rate are applied to the MSCC fast charging. The constraints of the optimization include temperature and cell voltage, which are applied to prevent thermal runway and reduce the capacity fade. The optimized charging current profile based on various initial temperatures, ambient temperatures, and heat transfer coefficients will be compared. In addition, the effect of constraints on optimization results will be discussed.

To study the effect of fast charging based on the battery dynamics, the electrochemical model first proposed by Newman et al. has been addressed. Even though the electrochemical model is not suitable for online application, the results can serve as a benchmark to evaluate and improve an existing online algorithm for battery fast charging optimization. However, few of those works using electrochemical models discussed the effect of fast charging strategies on battery electrochemical and thermal behavior, as well as charging energy efficiency under various charging current patterns.

Based on dynamic programming and electrochemical thermal model, this research proposes a new method to optimize charging current profile under various constraints and different optimization goals, which are useful for fast charging application of lithium-ion batteries on electric vehicles.