This paper cautions that the adoption of electric vehicles with the aim of reducing greenhouse gas emissions must balance that beneficial effect against increased water consumption. It recommends battery electric vehicles charged by solar energy as the best solution.
Accurate health estimation and lifetime prediction of lithium-ion batteries are crucial for durable electric vehicles. Early detection of inadequate performance facilitates timely maintenance of battery systems. This reduces operational costs and prevents accidents and malfunctions. Recent advancements in “Big Data” analytics and related statistical/computational tools raised interest in data-driven battery health estimation. Here, we will review these in view of their feasibility and cost-effectiveness in dealing with battery health in real-world applications.
