Economic and environmental values of electric vehicle batteries in Thailand utilizing system dynamics modeling and life cycle assessment approaches

The rapid global expansion of battery electric vehicles (BEVs) has led to an increase in retired EV batteries (REVBs), posing significant environmental challenges worldwide. Thailand, influenced by government incentives and technological advancements in EV batteries (EVBs), has seen a rise in BEV adoption, resulting in higher number of REVBs. Effective end-of-life (EOL) management strategies, including remanufacturing, repurposing, and recycling, are essential to mitigate environmental impacts and promote a circular economy. This research examines the environmental impacts and feasibility of EOL management of REVBs utilizing life cycle assessment (LCA) and system dynamics (SD) modeling approaches. The LCA method is utilized to assess the key environmental impacts associated with EOL management of REVB, including CO2eq emissions, human toxicity, terrestrial acidification, particulate matter formation, photochemical oxidant formation, water depletion, metal depletion, ozone depletion, and fossil fuel depletion. Normalized impact scores for different EOL management strategies are calculated in the LCA analysis and combined to achieve the final impact scores. The LCA results revealed that recycling process is the best EOL management process based on the environmental perspective. It gives the best final impact score of -279, presenting a significant reduction in the environmental impacts. The research also develops causal loop diagrams and an SD model to analyze the dynamic interactions among factors influencing EOL management. The benefits and costs, including environmental costs, are input in the SD model to select suitable EOL management strategies for implementation using the net present value (NPV) and internal rate of return (IRR). The simulation results revealed that the remanufacturing process is the most suitable EOL management process based on economic and environmental perspectives. It yields the highest IRR value of 45% in the next 30 years. Repurposing-only and remanufacturing plus repurposing strategies are also recommended for implementation as they yield the IRR values of 35 and 26% at the end of year 30. The sensitivity analysis was performed to validate the developed SD model and examine long-term strategies to enhance EOL management of REVBs in Thailand. The results suggest that the privilege parking, lithium reserve discovery rate, buyback cost, and human toxicity cost are major contributors to the feasibility of the EOL management project. The integration of these strategies promises an effective REVB management, reduces environmental footprints, and supports the sustainable growth of the Thai automotive sector in the long term.