Optimizing PHEV Battery Capacity with Battery Degradation

Plug-in hybrid electric vehicles (PHEVs) operate using both electricity and liquid fuel, offering emissions reduction while eliminating driving-range concerns. Determining the optimal electric range or battery capacity is crucial for the total cost of ownership, decarbonization potential, and battery material demand. However, the effect of battery degradation has not been incorporated into market-oriented range-optimization studies. This paper extends the existing MOR-PHEV range optimization model by integrating both cycle-based and calendar-based battery degradations. The results show meaningful optimization benefits, reducing consumer ownership cost by approximately $3000–5000. The optimal solution—defined by the minimized lifetime cost and the optimal battery capacity—is robust across the key external parameters. Intertwined with certain factors, battery degradation can have a significant impact on the optimal battery capacity. Particularly, at faster cycle-based degradation, high driving intensity and high CS efficiency can lead to optimization tipping points, where the degradation effect is so significant that the consumer is better off by choosing a small-battery PHEV (or HEV if the choice space expands beyond PHEV) in order to fully degrade the battery faster, totally avoid the charging behavior cost earlier, and maximally benefit from the high CS efficiency earlier. This points to the importance of reducing the cycle-based degradation coefficient and improving the vehicle energy efficiency and charging convenience. One basis point (0.01%) reduction in the cycle-based degradation coefficient is estimated to reduce the optimal battery capacity by 4.9–5.2 kWh and increase consumer value by $275–497, depending on the battery unit cost. These are useful insights into decision-making regarding battery technology R&D, battery chemistry roadmaps, critical material supply risks, and EV product strategies. While the findings in the study scope depend on assumptions of consumer behavior, battery degradation, vehicle efficiency and charging infrastructure, the expanded MOR-PHEV provides a systematic framework for considering different assumptions in support of user-defined decision context and discussing future research.