Sustainability of Electric Vehicles Using Artificial Intelligence

Abstract

Electric vehicles (EVs) are widely regarded as a more environmentally sustainable transportation option compared to traditional internal combustion engine vehicles. However, concerns persist regarding the sustainability impacts of EV battery manufacturing, specifically the mining of lithium used in lithium-ion batteries. This literature review examines the potential for artificial intelligence (AI) to improve the sustainability of lithium mining and battery manufacturing for EVs. An extensive literature search yielded insights into the environmental impacts of lithium mining such as high water usage, carbon emissions, and soil contamination. These impacts present a challenge to the sustainability narrative of EVs. However, researchers have identified numerous applications for AI across the lithium-ion battery supply chain that could mitigate these effects. From optimizing mineral exploration and mining operations to recycling spent batteries, AI solutions show promise to reduce the lifecycle impacts of lithium-ion batteries. Additional research is still needed to quantify these potential improvements and implement AI responsibly. Furthermore, technology alone cannot address the complex socio-economic challenges associated with lithium mining. Ultimately, a combination of technological innovation and ethical, inclusive resource management will be required to truly transition to sustainable EV mobility. Keywords: electric vehicles, lithium-ion batteries, lithium mining, sustainability, artificial intelligence.