scholarly journals Validation of Wireless Battery Management System (wBMS) – Gen2

2021 ◽  
Vol 23 (06) ◽  
pp. 816-825
Author(s):  
Mr. Chetan ◽  
◽  
Mrs. Sujatha Hiremath ◽  
Keyword(s):  
Management System ◽  
Battery Management System ◽  
Battery Management ◽  
Human Errors ◽  
Electric Cars ◽  
Equipment Manufacturer ◽  
Health Report ◽  
Front End ◽  
Python Programming ◽  
Number Of Iterations

Wireless Battery Management System (wBMS) is a primary enabler for the widespread adoption of electric cars, allowing auto Original Equipment Manufacturer (OEMs) to avoid having to rework complicated wiring diagrams for each new car and ensuring battery scalability. This article mainly focuses on the validation of an end-to-end wBMS system by performing several tests like Packet Transfer Ratio (PTR) for different configuration files, developing and implementing a health report application that generates health report in real-time, automating the process of OTA (Over the Air) upgrade which also includes automation of configuring the front-end application using a python programming language. The main intention behind developing the script to automate the OTA upgrade and health report application is to reduce the time consumed to test the system, reduce human errors, and perform the tests for any number of iterations.

Implementation of the Li-Ion Battery Management System Based on DS2438

2015 ◽  
Vol 733 ◽  
pp. 714-717 ◽  
Author(s):  
Ping Yang ◽  
Hou Yu Yu ◽  
Yong Gang Yan
Keyword(s):  
Management System ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Electric Cars ◽  
Power Battery ◽  
Electric Vehicle Battery ◽  
Li Ion

In order to ensure good performance and extend the lifetime of li-ion batteries in electric cars, effective real-time monitoring and management must be valued. This paper designs an electric vehicle battery management system based on a smart battery monitoring chip, DS2438. It integrates the measurement of battery's temperature, voltage, current, and power as a whole, which not only simplifies the circuit, but also saves system cost. The battery’s SOC (State Of Charge) can be easily estimated and displayed in this design. It improves the reliability of power battery pack and prolonged its life, which can be used as reference to battery management system design and application.

DESIGN OF BATTERY MANAGEMENT SYSTEM FOR ELECTRIC VEHICLE BATTERY-BASED HYBRID METAL-ORGANIC (SOL-GEL) LITHIUM MANGANATE (LiMn2O4)

2016 ◽  
Vol 6 (1) ◽  
pp. 19
Author(s):  
Wisnu Ananda ◽  
Mehammed Nomeri
Keyword(s):  
Electric Vehicle ◽  
Management System ◽  
Sol Gel ◽  
Lithium Ion ◽  
Support Vector ◽  
Battery Management System ◽  
Battery Management ◽  
Electric Cars ◽  
Electric Vehicle Battery ◽  
Li Ion

Battery-powered Electric Vehicles (BEVs) such as electric cars, use the battery as the main power source to drive the motor, in addition to lighting, horn, and other functions. Currently, Balai Besar Bahan dan Barang Teknik (B4T) has been conducting research in Lithium-ion (Li-ion) battery prototype for an electric vehicle. However, the management system in accordance with the electrical characteristics of the battery prototype is still not available. Thus, to integrate the battery prototype with electrical components of the electric vehicle, it is necessary to design Battery Management System (BMS). Two important battery parameters observed are State of Charge (SOC) and State  of  Health  (SOH).  The  method  used  for  SOC  was  Coulomb  Counting.  SOH  was  determined  using  a combination between Support Vector Machine (SVM) and Relevance Vector Machine (RVM). Based on the experiments by using BMS, the battery performance could be more controlled and produces a linear curve of SOC and SOH.Keywords: Battery, electric vehicle, Battery Management System (BMS), Lithium-ion (Li-ion).

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 Design of a Modular Battery Management System for Electric Motorcycle

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3532
Author(s):  
Hung-Cheng Chen ◽  
Shin-Shiuan Li ◽  
Shing-Lih Wu ◽  
Chung-Yu Lee
Keyword(s):  
Temperature Measurement ◽  
Management System ◽  
Battery Management System ◽  
Battery Management ◽  
Voltage Measurement ◽  
Mixed Signal ◽  
Discharge Temperature ◽  
Charging Current ◽  
Battery Module ◽  
Signal Processor

This paper proposes a modular battery management system for an electric motorcycle. The system not only can accurately measure battery voltage, charging current, discharging current, and temperature but also can transmit the data to the mixed-signal processor for battery module monitoring. Moreover, the system can control the battery balancing circuit and battery protection switch to protect the battery module charging and discharging process safety. The modular battery management system is mainly composed of a mixed-signal processor, voltage measurement, current measurement, temperature measurement, battery balancing, and protection switch module. The testing results show that the errors between the voltage value measured by the voltage measurement module and the actual value are less than 0.5%, about 1% under the conditions of different charging and discharging currents of 9 A and 18 A for the current measuring module, less than 1% for the temperature measurement module; and the battery balancing in the battery management system during the charging process. When the module is charged at 4.5 A for about 805 s, each cell of the battery has reached the balancing state. Finally, the testing results validate that the modular battery management system proposed in this paper can effectively manage the battery balancing of each cell in the battery module, battery module overcharge, over-discharge, temperature protection, and control.

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