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 Development of Life-cycle Detection and Extending Function for Reusing Automotive Lithium-ion Battery – Verified in 52V LiMnNiCoO2 Platform

2020 ◽  
Author(s):  
Wu-Yang Sean ◽  
Ana Pacheco
Keyword(s):  
Life Cycle ◽  
Lithium Ion Battery ◽  
Management System ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Cycle Detection

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.

scholarly journals Designing of Lithium - Ion Battery Pack Rechargeable on a Hybrid System with Battery Management System (BMS) for DC Loads of Low Power Applications – A Prototype Model

2021 ◽  
Vol 2089 (1) ◽  
pp. 012017
Author(s):  
Ramu Bhukya ◽  
Praveen Kumar Nalli ◽  
Kalyan Sagar Kadali ◽  
Mahendra Chand Bade
Keyword(s):  
Lithium Ion Battery ◽  
Management System ◽  
Short Circuit ◽  
Lithium Ion ◽  
Battery Pack ◽  
Prototype Model ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion

Abstract Now a days, Li-ion batteries are quite possibly the most exceptional battery-powered batteries; these are drawing in much consideration from recent many years. M Whittingham first proposed lithium-ion battery technology in the 1970s, using titanium sulphide for the cathode and lithium metal for the anode. Li-ion batteries are the force to be reckoned with for the advanced electronic upset in this cutting-edge versatile society, solely utilized in cell phones and PC computers. A battery is a Pack of cells organized in an arrangement/equal association so the voltage can be raised to the craving levels. Lithium-ion batteries, which are completely utilised in portable gadgets & electric vehicles, are the driving force behind the digital technological revolution in today’s mobile societies. In order to protect and maintain voltage and current of the battery with in safe limit Battery Management System (BMS) should be used. BMS provides thermal management to the battery, safeguarding it against over and under temperature and also during short circuit conditions. The battery pack is designed with series and parallel connected cells of 3.7v to produce 12v. The charging and releasing levels of the battery pack is indicated by interfacing the Arduino microcontroller. The entire equipment is placed in a fiber glass case (looks like aquarium) in order to protect the battery from external hazards to design an efficient Lithium-ion battery by using Battery Management System (BMS). We give the supply to the battery from solar panel and in the absence of this, from a regular AC supply.

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

Performance Evaluation of an Extended Kalman Filter for State Estimation of a Pseudo-2D Thermal-Electrochemical Lithium-Ion Battery Model

2015 ◽  
Author(s):  
Shi Zhao ◽  
Adrien M. Bizeray ◽  
Stephen R. Duncan ◽  
David A. Howey
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Lithium Ion Battery ◽  
Extended Kalman Filter ◽  
Lithium Ion ◽  
Low Noise ◽  
Particle Model ◽  
Battery Management System ◽  
Battery Management ◽  
Voltage Measurement

Fast and accurate state estimation is one of the major challenges for designing an advanced battery management system based on high-fidelity physics-based model. This paper evaluates the performance of a modified extended Kalman filter (EKF) for on-line state estimation of a pseudo-2D thermal-electrochemical model of a lithium-ion battery under a highly dynamic load with 16C peak current. The EKF estimation on the full model is shown to be significantly more accurate (< 1% error on SOC) than that on the single-particle model (10% error on SOC). The efficiency of the EKF can be improved by reducing the order of the discretised model while maintaining a high level of accuracy. It is also shown that low noise level in the voltage measurement is critical for accurate state estimation.

Research on a Battery Balancing Method for Lithium-Ion Battery Pack of Electric Vehicle

2014 ◽  
Vol 986-987 ◽  
pp. 1842-1845
Author(s):  
Yi Ning Chen ◽  
Yu Gui ◽  
Hong He
Keyword(s):  
Electric Vehicle ◽  
Topological Structure ◽  
Management System ◽  
Capacity Utilization ◽  
Lithium Ion ◽  
Battery Pack ◽  
Utilization Rate ◽  
Battery Management System ◽  
Battery Management ◽  
Key Technology

As the key technology of the electric vehicle, more and more research on battery management system has been done. And the balancing technology is the important part of battery management system. In this paper, a multi-inductor balancing method based on the Buck-Boost topological structure is used to improve batteries’ inconsistencies by obtaining parameters of the battery pack in real time. The proposed balancing method can improve batteries’ inconsistencies so as to increase the capacity utilization rate of the battery pack and prolong the battery lifespan. And in this paper a series of bench experiments were done to examine the effectiveness of the balancing method.

scholarly journals Battery management system on electric bike using Lithium-Ion 18650

2019 ◽  
Vol 10 (3) ◽  
pp. 1529
Author(s):  
Soeprapto Soeprapto ◽  
Rini Nur Hasanah ◽  
Taufik Taufik
Keyword(s):  
Management System ◽  
Lithium Ion ◽  
Cell Voltage ◽  
Battery Pack ◽  
Maintenance Cost ◽  
Average Error ◽  
Battery Management System ◽  
Battery Management ◽  
The Individual ◽  
Electric Bike

<span>Electric bike (E-Bike) is a bicycle driven using an electric motor and uses batteries as the energy source. It is environmentally friendly as no exhaust gas is resulted during its operation. More than one battery is normally required, being arranged in series or in parallel connection. Over limit or overloaded conditions of battery usage will reduce the lifecycle of battery, speed up its replacement and add to the maintenance cost of electric bike. This paper proposes the prevention of such degrading condition using a tool to manage the battery usage both during the charging and discharging process. The proposed electronic Battery Management System (BMS) serves to regulate, monitor, and maintain the condition of batteries to prevent any possible damage. The resulted BMS design could provide a well balancing action in a battery system consisting of 13 cells utilizing the cell-to-cell active balancing method. The test results showed that the proposed BMS could monitor the individual cell voltage with an average error of 0.032 V (0.824</span><span lang="IN">%</span><span>), while reading the charge and discharge current with an average error of 0.04 A (</span><span lang="IN">6.25%</span><span>), and the battery pack temperature with an average error of 1.21<sup>o</sup>C (</span><span lang="IN">2.9%</span><span>). Additionally, the BMS could offer a functional battery pack protection system from conditions such as undervoltage, overvoltage, overheat, and overcurrent.</span>

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.

Maximizing Battery Life and Usable Capacity With Battery Management System in Electric Vehicles

2017 ◽  
Author(s):  
Zoltán Szeli ◽  
Gábor Szakállas ◽  
Ferenc Szauter
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Active Cell ◽  
Battery Pack ◽  
Research Centre ◽  
Battery Life ◽  
Battery Management System ◽  
Battery Management ◽  
Cost Weight ◽  
Cell Balancing

In terms of the electric vehicles is an important issue of sizing a battery pack. The designer must take account of parameters such as cost, weight and durability. We can optimize these parameters with the help of a battery management system with integrated active cell balancing function. The article describes the development of a battery management system that developed by the Research Centre of Vehicle Industry at Széchenyi István University, Győr, Hungary.

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