Design on Electric Vehicle Battery Management System with FlexRay Bus

2015 ◽  
Vol 789-790 ◽  
pp. 784-790
Author(s):  
Jian Kun Peng ◽  
Hong Wen He ◽  
Deng Pan
Keyword(s):  
Electric Vehicle ◽  
Management System ◽  
Fault Tolerant ◽  
Estimation Method ◽  
Battery Management System ◽  
Battery Management ◽  
Soc Estimation ◽  
Electric Vehicle Battery ◽  
Bench Experiment ◽  
Li Ion

FlexRay bus is considered as a more promising bus in the future with the performance of real-time, scalable, and fault-tolerant. In this paper we will design an electric vehicle battery management system (BMS) based on FlexRay bus, including the hardware design, the SoC estimation method, FlexRay protocol design and software development. The test bench experiment results show the system design is reasonable and feasible.Keywords- FlexRay, BMS, Li-ion battery,SoC, Design

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 Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 446 ◽  
Author(s):  
Muhammad Umair Ali ◽  
Amad Zafar ◽  
Sarvar Hussain Nengroo ◽  
Sadam Hussain ◽  
Muhammad Junaid Alvi ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Management System ◽  
Lithium Ion ◽  
State Of Charge ◽  
Estimation Methods ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Li Ion

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.

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.

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