Programmable logic controller based lithium-ion battery management system for accurate state of charge estimation. (July 2021)

• Record Type: Journal Article
• Authors: Mohammed, Nabil; Saif, Ahmed Majed
• Is Part Of: Computers & electrical engineering. Volume 93(2021)
• Publication Date: 2021-07
• Subjects: SOC -- Coulomb Counting -- Open circuit voltage -- Lithium ion battery -- Battery energy storage system -- PLC -- HMI/SCADA; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107306
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Lithium-ion batteries (LIBs) are extensively used in many applications; from portable devices to major energy applications such as battery energy storage systems (BESSs). Their packs are usually equipped with accurate battery management systems (BMSs) to maintain the safe operation of the cells. To overcome the drawbacks of BMSs implemented with micro-controllers such as low reliability, low flexibility, and difficulties in troubleshooting, a programmable logic controller (PLC) based BMS is proposed in this paper. Furthermore, the accurate real-time estimation algorithm for state of charge (SOC) is achieved based on the combination of Coulomb Counting (CC) and the open-circuit voltage ( V O C ) methods. The advantage of including V O C method is to initialize SOC and performing frequent recalibration when the battery is in standby mode. Hence, the posed accumulated errors problem from using CC method are fully mitigated. Siemens TIA Portal software is used to implement the proposed PLC-based BMS, where SIMATIC STEP 7 and SIMATIC WinCC are utilized for facilitating the code development and monitoring using human–machine interface (HMI), respectively. Presented results prove the effectiveness of the proposed PLC-based BMS. Future research directions related to PLC-Based BMS are lastly discussed.