An Economic Evaluation Model of Predictive Maintenance Technology for Lithium-Ion Batteries

The failures of Lithium-ion batteries have aroused unexpected safety accidents. To improve the battery availability and reduce losses, predictive maintenance technology can be employed for failure prediction and health management. Nevertheless, the additional cost of establishing the predictive maintenance system is an obstruction to its widespread applications. This paper aims to conduct a life-cycle economic evaluation of predictive maintenance technology by considering the incremental costs and benefits. First, we constructed a quantitative relationship model between failure modes and benefits of Lithium-ion battery systems based on failure mode, mechanism and effect analysis to determine the incremental benefit. Then we established a cost-benefit analysis model by using system dynamics. Secondly, to optimize the cost investment strategy of predictive maintenance technology, we raised an enterprise-government evolutionary game model based on the information asymmetry between players. Eventually, we conducted the sensitivity analysis of the static subsidy strategy. The proposed methodology is serviceable to optimize the decision-making of technology investment.