Intelligent BMS Solution Using AI and Prognostic SPA

Abstract

This paper presents a Novel, Low cost and Efficient Intelligent Battery Management Solution (iBMS) for Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV). The solution provides a comprehensive topology for identifying the State of Charge (SOC), State of Health (SOH), charging and discharging including isolation of defective identified battery cell from healthy ones. The highly modular and scalable solution uses Bi-directional, 4 quadrant DC–DC converter; a non-isolated four switch topology design for the charging/discharging and cell cut off (infected cell), an Artificial Intelligence (AI) module using Fuzzy Logic (FL) and Signature Pattern Analysis (SPA) for envisaging the Battery stack health. The proposed design offers an affordable On-Board monitoring & diagnostics module leveraging the above intelligent modules and Impedance Analysis. This circumvents the need of further diagnostic tools; makes the system highly portable, Scalable for any chemical composition of battery cell and considerably extend the life cycle of EV/HEV battery stacks. In this paper, we will review some of the issues and associated solutions for battery thermal management and what information is needed for proper design of battery management systems. We will discuss about the issues related to impedance management which affects the battery life.

F2012-B04-008