A Design Methodology for Lithium-Ion Battery Management System and its Application to an Autonomous Underwater Vehicle

2011 ◽  
Vol 383-390 ◽  
pp. 7175-7182 ◽  
Author(s):  
Chao Shen ◽  
Lei Wan

Battery management system (BMS) in autonomous underwater vehicle (AUV) not only can measure the main parameters of battery packs such as current, voltage, and temperature, but also estimate the state of charge (SOC) of battery packs. This paper proposes a broad approach for the design of battery management system. The new design can improve the cycle life and safety capability. With the model well designed, the parameters required are obtained and the SOC estimation is completed. Extended Kalman filter (EKF) was chosen to make the last estimate with the reliable battery model which was used to the non-linear system to estimate SOC and suitable for AUV applications. The experiments results prove that the data measured by battery management system have high precision and reliability. The estimated error of SOC was also small, which was better than other approaches for estimate.

2011 ◽  
Vol 201-203 ◽  
pp. 2427-2430
Author(s):  
Yuan Liao ◽  
Ju Hua Huang ◽  
Qun Zeng

According to the features of lithium ion battery packs, a distributed battery management system (BMS) for battery electric vehicle (BEV) is designed in this article. The BMS consists of a master module with several sampling modules. The kernel of master module is TMS320C2812 digital signal processor, and the kernel of sampling module is P87C591 singlechip. The main functions of master module include estimation of state of charge (SOC) and security management of lithium ion battery packs, and the main functions of sampling module include battery information collection and CAN bus based communication. SOC estimation method based on Extended Kalman filtering (EKF) theory is adopted in this article to precisely estimate the SOC of lithium ion battery packs.


Author(s):  
Suchitra D ◽  
Rajarajeswari R ◽  
Dhruv Singh Bhati

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.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 446 ◽  
Author(s):  
Muhammad Umair Ali ◽  
Amad Zafar ◽  
Sarvar Hussain Nengroo ◽  
Sadam Hussain ◽  
Muhammad Junaid Alvi ◽  
...  

Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.


2013 ◽  
Vol 772 ◽  
pp. 725-730
Author(s):  
Xu Jun Li ◽  
Da Liu ◽  
Rui Yan ◽  
Yue Qiu Gong ◽  
Yong Pan

A battery management system (BMS) is described along with important features for protecting and optimizing the performance of large 18650 lithium power battery packs. Of particular interest is the selection of many cells, that is, according to the system needs to choose healthy cells into the system to run. In order to shorten the cycle of research, the paper proposed a BMS based on virtual instrument (VI) data acquisition system. It can monitor parameters such as monomer voltage, total voltage, current, temperature, estimating state of charge (SOC) etc, and it also can control switch when a parameter exceeds the allowed range, the corresponding monomer cell will be automatically cut off the switch and alarm. Experimental results are included for a pack of seven 2.2 Ah (amp-hour) 18650 lithium power cells. It can monitor the status of the lithium-ion battery pack according to the security metrics of 18650 power lithium cells. It can control other types of power batteries by means of modified index.


Author(s):  
L. Rimon ◽  
Khairul Safuan Muhammad ◽  
S.I. Sulaiman ◽  
AM Omar

<span>Robustness of a battery management system (BMS) is a crucial issue especially in critical application such as medical or military. Failure of BMS will lead to more serious safety issues such as overheating, overcharging, over discharging, cell unbalance or even fire and explosion. BMS consists of plenty sensitive electronic components and connected directly to battery cell terminal. Consequently, BMS exposed to high voltage potential across the BMS terminal if a faulty cell occurs in a pack of Li-ion battery. Thus, many protection techniques have been proposed since last three decades to protect the BMS from fault such as open cell voltage fault, faulty cell, internal short circuit etc. This paper presents a review of a BMS focuses on the protection technique proposed by previous researcher. The comparison has been carried out based on circuit topology and fault detection technique</span>


2020 ◽  
Author(s):  
Wu-Yang Sean ◽  
Ana Pacheco

Abstract For reusing automotive lithium-ion battery, an in-house battery management system is developed. To overcome the issues of life cycle and capacity of reused battery, an online function of estimating battery’s internal resistance and open-circuit voltage based on adaptive control theory are applied for monitoring life cycle and remained capacity of battery pack simultaneously. Furthermore, ultracapacitor is integrated in management system for sharing peak current to prolong life span of reused battery pack. The discharging ratio of ultracapacitor is adjusted manually under Pulse-Width-Modulation signal in battery management system. In case study in 52V LiMnNiCoO2 platform, results of estimated open-circuit voltage and internal resistances converge into stable values within 600(s). These two parameters provide precise estimation for electrical capacity and life cycle. It also shows constrained voltage drop both in the cases of 25% to 75% of ultracapacitors discharging ratio compared with single battery. Consequently, the Life-cycle detection and extending functions integrated in battery management system as a total solution for reused battery are established and verified.


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