臺灣博碩士論文加值系統

本論文主要研究目的為完成『A Study of the Diagnosis of Peripheral Circuits in the Battery Module Using 8-Series of 3.2V/50Ah LiFePO4 Energy Storage System』，本系統包含8顆串聯磷酸鋰鐵電池、微控制器、電池採樣單元、電流感測單元、高壓繼電器。
本論文利用SPI通訊連接電池採樣單元、電流感測單元來獲取電池狀態（電壓、電流、溫度），通過計算驗證數據的準確性，並將系統時脈與固定獨立時脈源進行比較以確保時脈的準確性，針對電池電壓數據進行採集以確認電池是否異常（開路或短路），並通過GPIO狀態與高壓繼電器的配合診斷高壓繼電器是否在應關斷時發生沾黏，當系統診斷出異常時會通過UART通訊傳輸異常詳細資訊至遠端資料庫，並依照異常嚴重性進行分級，第一級為需要立即處理之異常、第二級為可稍後處理之異常，讓使用者可以即時獲得系統發生異常的詳細資料，並根據分級進行異常的處理。
關鍵字：磷酸鋰鐵電池、自我診斷、電池管理系統、異常狀態紀錄

The primary objective of this thesis is to complete "A Study of the Diagnosis of Peripheral Circuits in the Battery Module Using 8-Series of 3.2V/50Ah LiFePO4 Energy Storage System". This system includes 8-series LiFePO4, a microcontroller, battery sampling units, current sensing units and high-voltage relays.
This thesis used SPI communication to connect the battery sampling unit and the current sensing unit to acquire the battery status (voltage, current, temperature). Data accuracy was verified through calculations, and the system clock was compared with a fixed independent clock to ensure precision. Battery voltage data was collected to detect whether there is an abnormality (open or short circuit). The state of the GPIO, in conjunction with high-voltage relays, diagnoses whether the relays are stuck when they should be off. When an abnormality was detected, detailed information is transmitted to a remote database via UART communication. Abnormalities are classified by severity: Level 1 is the level for abnormalities that require immediate handling, and Level 2 is for those that can be handled later. This allows users to promptly receive detailed information about system abnormalities and handle them according to their classification.
Keywords: LiFePO4, Self-Diagnosis, BMS, Abnormality Records

Honors and Conference Paper ii
Abstract (in Chinese) iii
Abstract (in English) iv
Acknowledgments vi
List of Figures ix
List of Tables xi
Contents xii
Chapter 1 Introduction 1
1.1 Background 2
1.2 Motivation 2
1.3 Thesis Structure 4
Chapter 2 Literature Review 5
2.1 Introduction to Battery Management Systems 5
2.1.1 Battery Status Monitoring 5
2.1.2 Peripheral Circuits and Fault Self-Diagnosis 6
2.1.3 Remote Battery Monitoring Interface 7
2.2 Lithium Iron Phosphate Battery（LiFePO4） 7
Chapter 3 Introduction to the Architecture of Peripheral Circuit Diagnostics for Battery Modules in Energy Storage Systems 9
3.1 8-Series 3.2V/50Ah Lithium Iron Phosphate Battery Pack 9
3.2 RH850 Microcontroller 10
3.3 ADBMS6815 Battery Sampling Unit 10
3.4 RAJ240090 Current Sensing Unit 11
3.5 Multi-Protocol Communication Module 12
3.6 HVC500B-24HOE2KF High-Voltage Relay 12
3.7 RTOS Real-Time Operating System 13
3.8 SPI Communication 14
3.9 UART Communication 14
Chapter 4 Experimental Procedure and Results 16
4.1 Hardware Setup of the Battery Management System 16
4.2 Software Development Environment and Functional Design of the Battery Management System 17
4.3 Experimental Diagnosis of SPI Communication Abnormalities in the ADBMS6815 Battery Sampling Unit 18
4.4 Experimental Diagnosis of System Clock Abnormalities 19
4.5 Experimental Diagnosis of Battery Pack Open Circuit/Short Circuit 19
4.6 Experimental Diagnosis of Current Abnormalities 20
4.7 Experimental Detection of GPIO High/Low, Relay Open Circuit, and Adhesion 21
4.8 Transmission of Diagnostic Results to Database and Display on Remote Monitoring Interface 21
4.9 Practical Verification and Application 22
Chapter 5 Conclusions 24
Chapter 6 Future Applications and Prospects 26
References 28
Figures 32
Tables 49
Biography 53

[1]A. K. M. A. Habib, M. K. Hasan, G. F. Issa, D. Singh, S. Islam, and T. M. Ghazal, "Lithium-Ion Battery Management System for Electric Vehicles: Constraints, Challenges, and Recommendations", in Batteries, vol.9, issue 3, (2023).
[2]H. A. Gabbar, A. M. Othman, and M. R. Abdussami, "Review of Battery Management Systems (BMS) Development and Industrial Standards", in Technologies, vol.9, issue 2, (2021).
[3]K. W. See, G. Wang, Y. Zhang, Y. Wang, L. Meng, X. Gu, N. Zhang, K. C. Lim, L. Zhao, and B. Xie, "Critical review and functional safety of a battery management system for large-scale lithium-ion battery pack technologies", in International Journal of Coal Science & Technology, vol.9, article number: 36, (2022).
[4]V. S. R. Kosuru, and A. K. Venkitaraman, "A Smart Battery Management System for Electric Vehicles Using Deep Learning-Based Sensor Fault Detection", in WEVJ, vol.14, issue 4, (2023).
[5]M. S. H. Lipu, M. S. Miah, T. Jamal, T. Rahman, S. Ansari ,M. S. Rahman, R. H. Ashique, A. S. M. Shihavuddin, and M. N. Shakib, "Artificial Intelligence Approaches for Advanced Battery Management System in Electric Vehicle Applications: A Statistical Analysis towards Future Research Opportunities", in Vehicles, vol.6, issue 1, (2024).
[6]R. Xiong, W. Sun, Q. Yu, F. Sun, "Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles", in Applied Energy, vol.279, (2020).
[7]Q. Liu, J. Ma, X. Zhao, and K. Zhang, "Power Battery Fault Diagnosis of Electric Vehicles Based on Modified Shannon Entropy in Real Scenarios", in Proceedings of China SAE Congress 2023: Selected Papers, pp1444-1445, (2023).
[8]D. Gunapriya, N. Pusphalatha, S. Sudharsan, S. Pandi, L. Catherine, V. Sharma and A. Alkhayyat, "An Exhaustive Investigation of Battery Management System (BMS) " in 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM), (2023).
[9]P. Liu, C. Lu, C. Wang, X, Wang, W. Xu, Y. Zhou, and H. Li, "Research Status and Development of Battery Management System", in Communications, Signal Processing, and Systems, pp. 1422–1429, (2021).
[10]M. K. Tran, S. Panchal, T. D. Khang, K. Panchal, R. Fraser, and M.Fowler, "Concept Review of a Cloud-Based Smart Battery Management System for Lithium-Ion Batteries: Feasibility, Logistics, and Functionality", in Batteries, vol.8, issue 2, (2022).
[11]R. Bustos, S. A. Gadsden, M. Biglarbegian, M. AlShabi, and S. Mahmud, "Battery State of Health Estimation Using the Sliding Interacting Multiple Model Strategy", in Energies, vol.17, issue 2, (2024).
[12]P. S. Rani, B. Jyothi, S. K. Nagoor, and S. Meghanadh, "Battery Monitoring System for Electric Vehicles ", in Control Applications in Modern Power Systems, pp291-300, (2024).
[13]Y. Xing, E. W. M. Ma, K. L. Tsui, and M. Pecht, "Battery Management Systems in Electric and Hybrid Vehicles", in Energies, vol.4, issue 11, (2011).
[14]K. Bhaskar, A. Kumar, J. Bunce, J. Pressman, N. Burkell, and C. D. Rahn, "Data-Driven Thermal Anomaly Detection in Large Battery Packs", in Batteries, vol.9, issue 2, (2023).
[15]J. D. Gotz, G. C. Guerrero, J. F. R. Espolador, S. H. Werlich, M. Borsato, and F. C. Corrêa, "Application of Anomaly Detection Algorithms in Lithium-Ion Battery Packs - A Case Study", in Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus Conference paper, pp.753-760, (2023).
[16]D. Shi, J. Zhao, C. Eze, Z. Wang, J. Wang, Y, Lian, and A. F. Burke, "Cloud-Based Artificial Intelligence Framework for Battery Management System", in Energies, vol.16, issue 11, (2023).
[17]S. Yang, X. Liu, S. Li, and C. Zhang, "Cloud Battery Management System", in Advanced Battery Management System for Electric Vehicles, pp.301-313, (2022).
[18]X. Cao, C. Ma, L. Luo, L. Chen, H. Cheng, R. S. Orenstein, and X. Zhang, "Nanofiber Materials for Lithium-Ion Batteries", in Advanced Fiber Materials, vol.5, pp.1141-1197, (2023).
[19]T. Sun, L. Wang, D. Ren, Z. Shi, J. Chen, Y. Zheng, X. Feng, X. Han, L. Lu, L. Wang, X. He, and M. Ouyang, "Thermal Runaway Characteristics and Modeling of LiFePO4 Power Battery for Electric Vehicles ", in Automotive Innovation, vol.6, pp.414-424, (2023).
[20]G. R. Molaeimanesh, S. M. Mousavi-Khoshdel , and A. B. Nemati, "Experimental analysis of commercial LiFePO4 battery life span used in electric vehicle under extremely cold and hot thermal conditions", in Journal of Thermal Analysis and Calorimetry, vol.143, pp.3137-3146, (2020).
[21]Q. Yu, L. Ma, S. Xiao, X. Du, L. Yang, C. Sun, L. Wang, S. Ruan, X. He, Y. Zhang, X. Yu, Y. Jiang, F. Tu, J. Xiang, W. Wan, C. Wang, Y. Xia, X. Xia, and W. Zhang, "Aging Mechanisms and Evolution Patterns of Commercial LiFePO4 Lithium-Ion Batteries ", in Journal of Electronic Materials, vol.53, pp.2842-2851, (2024).
[22]Renesas, RH850 F1L, Datasheet, (2016).
[23]Analog Devices, ADBMS6815, Datasheet, (2017).
[24]Renesas, RAJ240090, Datasheet, (2024).
[25]TDK Corporation, HVC500B-24HOE2KF, Datasheet, (2018).