Work

Inventory Strategies for Warranty Replacements of Electric Vehicle Batteries Considering Symmetric Demand Statistics

Year: 2025

Type: article

Abstract: Driven by growing environmental awareness and supportive regulatory frameworks, electric vehicles (EVs) are witnessing accelerating market penetration. However, a key consumer concern remains: the economic impact of battery degradation, manifesting as vehicle depreciation and diminished driving range. To alleviate this concern, EV manufacturers commonly offer performance-guaranteed free-replacement warranties, under which batteries are replaced at no cost if capacity falls below a specified threshold within the warranty period. This paper develops a symmetry-informed analytical framework to forecast time-varying aggregate warranty replacement demand (AWRD) and to design optimal battery inventory strategies. By coupling stochastic EV sales dynamics with battery performance degradation thresholds, we construct a demand forecasting model that presents structural symmetry over time. Based on this, two inventory optimization models are proposed: the Service-Level Symmetry Model (SLSM), which prioritizes reliability and customer satisfaction, and the Cost-Efficiency Symmetry Model (CESM), which focuses on economic balance and inventory cost minimization. Comparative analysis demonstrates that CESM achieves superior cost performance, reducing total cost by 20.3% while maintaining operational stability. Moreover, incorporating CESM-derived strategies into SLSM yields a hybrid solution that preserves service-level guarantees and achieves a 3.9% cost reduction. Finally, the applicability and robustness of the AWRD forecasting framework and both symmetry-based inventory models are validated using real-world numerical data and Monte Carlo simulations. This research offers a structured and symmetrical perspective on EV battery warranty management and inventory control, aligning with the core principles of symmetry in complex system optimization.

Source: Symmetry

DOI: 10.3390/sym17060928

Authors: Miaomiao Feng, Wei Xie, Xia Wang

Institutions: South China University of Technology, Fuzhou University, Guangzhou City University of Technology

Language: English

Topic: Supply Chain and Inventory Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896