SMART-LIC—Smart and Compact Battery Management System Module for Integration into Lithium-Ion Cell for Fully Electric Vehicles

2014 ◽  
pp. 97-106
Author(s):  
Jochen Langheim ◽  
Soufiane Carcaillet ◽  
Philippe Cavro ◽  
Martin Steinau ◽  
Olfa Kanoun ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Lithium Ion ◽  
Battery Management System ◽  
Battery Management ◽  
Lithium Ion Cell ◽  
System Module

Lithium-Ion Battery Health Prognosis Based on a Real Battery Management System Used in Electric Vehicles

2019 ◽  
Vol 68 (5) ◽  
pp. 4110-4121 ◽  
Author(s):  
Rui Xiong ◽  
Yongzhi Zhang ◽  
Ju Wang ◽  
Hongwen He ◽  
Simin Peng ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Management System ◽  
Lithium Ion ◽  
Battery Management System ◽  
Battery Management

scholarly journals A Survey of Wireless Battery Management System: Topology, Emerging Trends, and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2193
Author(s):  
Akash Samanta ◽  
Sheldon S. Williamson
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Lithium Ion ◽  
Future Research ◽  
Battery Management System ◽  
Battery Management ◽  
Implementation Cost ◽  
Future Developments ◽  
Emerging Trends ◽  
Depth Analysis

An effective battery management system (BMS) is indispensable for any lithium-ion battery (LIB) powered systems such as electric vehicles (EVs) and stationary grid-tied energy storage systems. Massive wire harness, scalability issue, physical failure of wiring, and high implementation cost and weight are some of the major issues in conventional wired-BMS. One of the promising solutions researchers have come up with is the wireless BMS (WBMS) architecture. Despite research and development on WBMS getting momentum more than a decade ago, it is still in a preliminary stage. Significant further upgradation is required towards developing an industry-ready WBMS, especially for high-power LIB packs. Therefore, an in-depth survey exclusively on WBMS architectures is presented in this article. The aim is to provide a summary of the existing developments as well as to present an informative guide to the research community for future developments by highlighting the issues, emerging trends, and challenges. In-depth analysis of the existing WBMS topologies will not only help the researchers to understand the existing challenges and future research scopes clearly but at the same time enthuse them to focus their research inclination in the domain of WBMS.

A cost effective accumulator management system for electric vehicles

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Suchitra D ◽  
Rajarajeswari R ◽  
Dhruv Singh Bhati
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Lithium Ion ◽  
Cost Effective ◽  
Battery Management System ◽  
Battery Management ◽  
Cell Parameters ◽  
Battery Design ◽  
Battery Packs ◽  
Cost Efficient

AbstractAn accumulator or battery is an energy storage cramped in an adaptable stockade. Lithium-ion batteries are commonly used in hybrid electric vehicles (HEV) and battery operated electric vehicles (BOEV) due to its eco-friendliness and increased efficiency. To maintain lithium batteries in the safe operating region and also to perform tasks like cell balancing, preventing thermal runaway, maintain the state of health, an effective battery management system (BMS) is required. The BMS should also communicate effectively between host devices and battery packs. This paper proposes a reliable, modular and cost-efficient BMS, which will emanate an alert when a fault occurs and thus preventing the battery from damage. An efficient control strategy has been proposed for charging and discharging of the battery pack. The thermal analysis of the lithium-ion battery used in this work is simulated using battery design studio (BDS) with the inclusion of a self-discharging effect. The proposed hardware setup also provides a provision for on-board diagnosis (OBD) and logging in the accumulator management system (AMS) to constantly monitor the cell parameters like voltage, current, and temperature. The live data display of AMS working is also shown during abnormal and normal conditions. Also, an attempt is made to use the design of proposed AMS for HEV.

scholarly journals Modeling and Simulation of Battery Management System (BMS) for Electric Vehicles

2021 ◽  
Vol 23 (06) ◽  
pp. 805-815
Author(s):  
Ravi P Bhovi ◽  
◽  
Ranjith A C ◽  
Sachin K M ◽  
Kariyappa B S ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Electric Vehicles ◽  
Management System ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Electric Cars

Electric cars have evolved into a game-changing technology in recent years. A Battery Management System (BMS) is the most significant aspect of an Electric Vehicle (EV) in the automotive sector since it is regarded as the brain of the battery pack. Lithium-ion batteries have a large capacity for energy storage. The BMS is in charge of controlling the battery packs in electric vehicles. The major role of the BMS is to accurately monitor the battery’s status, which assures dependable operation and prolongs battery performance. The BMS’s principal job is to keep track, estimate, and balance the battery pack’s cells. The major goals of this work are to keep track of battery characteristics, estimate SoC using three distinct approaches, and balance cells. Coulomb Counting, Extended Kalman Filter, and Unscented Kalman Filter are the three algorithms that will be implemented. Current is used as an input parameter to implement the coulomb counting method. In contrast to voltage and temperature, the current value is taken into account by the Extended and Unscented Kalman Filters. To calculate the state transition and measurement update matrix, these parameters are considered. This matrix will then be used to calculate SoC. Results of all the algorithms will be comparatively analyzed. MATLAB R2020a software is used for the simulation of different algorithms and SoC calculation. Three states of BMS are considered and they are Discharging phase, the Standby/resting phase, and the Charging phase. At the beginning of the Simulation, the SoC values of the cells were 80%. At the end of simulation maximum values of SoC of Coulomb counting, Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF) reached are 100%, 98.74%, and 98.46% respectively. After SoC Estimation, Cell balancing is also performed over 6 cells of the battery pack.

scholarly journals Desain Penyeimbangan Sel Baterai Lithium-Ion dengan Teknik Cell-to-Cell Charging Mode pada Battery Management System (BMS)

2021 ◽  
Vol 8 (1) ◽  
pp. 9-15
Author(s):  
Khaeruddin Khaeruddin ◽  
Wijono Wijono ◽  
Rini Nur Hasanah
Keyword(s):  
Management System ◽  
Lithium Ion ◽  
Battery Management System ◽  
Battery Management ◽  
Lithium Ion Cell ◽  
Charging Mode

Makalah ini membahas tentang penyeimbangan arus charging baterai lithium-ion pada BMS (Battery Management System) mobil listrik. Kondisi tidak seimbang pada saat proses pengisian baterai disebabkan karena salah satu baterai yang sudah terisi penuh sedangkan sebagiannya masih separuh atau bahkan hanya seperampat saja yang terisi. Kondisi ini dapat menyebabkan baterai cepat panas, serta melewati kondisi SOA (Safety of Area) sehingga menyebabkan kebakaran pada baterai. Pada penelitian ini, teknik cell-to-cell diusulkan untuk menyeimbangkan arus pengisian ke masing-masing sel baterai agar mendekati kondisi sama rata. Hasil simulasi menunjukan bahwa penggunaan teknik balancing cell-to-cell dapat menyeimbangkan sel baterai selama masa pengisian.  Kata kunci: Penyeimbangan, Sel, Baterai, Lithium-ion, Cell-to-cell, BMS.

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