Design Of Battery Management System Research Articles

Review on Design and Analysis of Battery Management System for Electric Vehicles

Abstract: In order to ensure effective functioning, the Batteries Management System (BMS) plays a crucial role in supervising and controlling the charging and discharge procedures of rechargeable battery packs within electric cars. Protection of the battery, preserving its dependability, and increasing its whole life are its fundamental goals. A range of monitoring methods, including as ambient temperature, voltage, and current monitoring, are used to maintain ideal battery conditions in order to do this. The use of microcontrollers in combination with analogue and digital sensors allows for efficient monitoring. In addition, this study investigates variables including battery maximum capacity, health condition, and charge state in an effort to offer thorough understandings of BMS features. Through the examination of these techniques, the research aims to anticipate and prepare for future difficulties related to BMS, while also addressing current concerns. An essential component of BMS functioning is evaluating the battery's state, involving factors like charge status, condition, and overall life status. The study provides a comprehensive analysis of state-of-the-art battery condition evaluation approaches, highlighting impending issues for BMS and offering workable solutions

Design and optimization of battery and thermal management system for AC photovoltaic energy module

The utilization of renewable energy sources has increased due to concerns about climate change. However, injecting the power from renewable energy sources into grid-tied systems is challenging. The techno-economic analysis a photovoltaic (PV) energy systems is investigated. As a result, this paper presents AC-PV module for Grid-Tied and Off-Grid Scenarios via optimization, modeling, and test results. Even though the output of a PV panel is DC voltage, a three-port inverter and a lithium-ion battery pack are integrated with the back of the PV panel. They are packaged as a PV system module that makes the module output have AC voltage. Therefore, an optimized AC-PV module can be a solution for residential and commercial use, which are grid-tied systems; it can be very efficient for those without access to electricity, which is an off-grid system. An integrated battery and thermal management strategy is crucial for this AC-PV module. In the article, the battery capacity optimization, the electrical and the thermal model of the battery pack, battery heat generation model are discussed by using stochastic analysis techniques; the battery test results are also obtained to identify the models’ parameters and a control algorithm is proposed to extract the battery information such as temperature, current, voltage, SoC and SoH of the battery pack.

Design and analysis of battery management system in electric vehicle

The usage of electric vehicles is gaining momentum in recent time’s thus providing support to the growth in sales of electric vehicles. The Battery management system is the most important aspect to ensure the smooth functioning of an electric vehicle. This research highlights some key statements on the background of electric vehicles. The increase in the overall growing importance of electric vehicles has also been explained in this work. Battery management system has an importance in the functioning of electric vehicles, thus presenting the key highlights of this article. The finding presents the importance of batteries and their type used in EVs. The simulation results of the Lithium battery cell – 1 RC, 2 RC equivalent circuit parameters such as charging current, terminal voltage, state of charge, and battery current have been simulated and analysed in Matlab. The future scope of BMS and its development has been discussed.

Design and Analysis of Battery Management System for Electric Vehicles

Abstract: This article presents a design for both the hardware and software components of the BMS, enabling battery monitoring and management. The Battery Management System (BMS) is a fundamental component of electric vehicles, primarily utilized to ensure battery safety and enhance battery lifespan. The hardware component encompasses the design of voltage acquisition circuitry, second-order filtering circuitry, sampling and holding circuitry, CAN bus communication circuitry, and other relevant features. The software section comprises subroutines for battery information collection, equalization circuitry, SOC estimation, and other relevant features. The BMS developed in this study successfully collects voltage, temperature, current, and other relevant information, and accurately estimates SOC and other crucial parameters. Testing confirmed that the battery management system precisely collects battery voltage, current, and temperature information, while the SOC estimation achieves a relatively high degree of accuracy.

Accelerating the transition to cobalt-free batteries: a hybrid model for LiFePO4/graphite chemistry

The increased adoption of lithium-iron-phosphate batteries, in response to the need to reduce the battery manufacturing process’s dependence on scarce minerals and create a resilient and ethical supply chain, comes with many challenges. The design of an effective and high-performing battery management system (BMS) for such technology is one of those challenges. In this work, a physics-based model describing the two-phase transition operation of an iron-phosphate positive electrode—in a graphite anode battery—is integrated with a machine-learning model to capture the hysteresis and path-dependent behavior during transient operation. The machine-learning component of the proposed “hybrid” model is built upon the knowledge of the electrochemical internal states of the battery during charge and discharge operation over several driving profiles. The hybrid model is experimentally validated over 15 h of driving, and it is shown that the machine-learning component is responsible for a small percentage of the total battery behavior (i.e., it compensates for voltage hysteresis). The proposed modeling strategy can be used for battery performance analysis, synthetic data generation, and the development of reduced-order models for BMS design.

A Review on Design and Development of Battery Management System for Electric Vehicle

A Review on Design and Development of Battery Management System for Electric Vehicle

A novel MIMO BMS design for user-friendly replacement of batteries

The proposed design introduces an innovative Multiple-Input Multiple-Output (MIMO) based Battery Management System (BMS) design that facilitates convenient battery replacement in battery packs. The technology allows for real-time monitoring of battery health through separate communication channels, making it easier to identify and replace batteries without the need for complicated disassembly. Granular control of charging/discharging and cell balancing allows for the achievement of enhanced safety and increased pack performance.

SOC estimation of lithium battery based on the combination of electrical parameters and FBG non-electrical parameters and using NGO-BP model

Accurately estimating of the state of charge (SOC) of lithium batteries is of great significance for improving the service life and utilization efficiency of lithium batteries. In this paper, fiber Bragg grating (FBG) sensors are used to capture the offset of the FBG central wavelength caused by strain and temperature during the charging and discharging process of lithium batteries, and the current state of charge of lithium batteries is obtained through the combination of electrical parameters and FBG non-electrical parameters.A battery monitoring experimental system was established, and the comparison of wavelength offset collected by PDMS packaged FBG and bare FBG during the charging and discharging process of lithium batteries was discussed. The prediction results were compared by temperature compensating the central wavelength offset collected during the charging and discharging of lithium batteries, then introduced BP neural network and optimized NGO- BP neural network regression models for training to compare the prediction effects, the results of which point to the fact that in terms of regression model performance and improvement of FBG non-electrical parameters on model performance, the various indicators predicted by NGO-BP are stronger than those predicted by BP. After adding FBG non-electrical parameters, both the BP regression model and the NGO-BP regression model showed remarkable improvement in RMSE, MAE, and R2 compared to the purely electrical parameters, and the best prediction method for the NGO-BP non-purely electrical parameters, with RMSE of 0.0201 and MAE of 0.0154, which decreased by 77.94% and 73.12% respectively compared to the BP pure electrical parameter prediction method, and R2 of 0.9988, which increased by 5.88%, thus the joint accurate estimation of lithium battery SOC by electrical measurement characteristics and FBG non-electrical parameters is basically realized, which brings values for the design and development of battery management system.

Design and Application of Station Power Supply System for Lithium Iron Phosphate Battery Based on Power Exchange Operation

Based on the engineering application design and development of the power supply system of lithium iron phosphate battery pack in the operation and maintenance mode, this paper conducts the application research from four aspects of battery quantity selection, capacity calculation selection, battery management system design, battery pack modular design, etc. The design scheme of the lithium iron phosphate power supply system is formulated, and the matching battery management system is designed. A universal lithium iron phosphate battery module with an “N+1” redundant configuration is developed to improve the maintenance efficiency of the battery pack. It reliably supports the substation power changing operation and maintenance mode and ensures the reliability and operation safety of the substation power supply system.

Designing a battery Management system for electric vehicles: A congregated approach

In many high-power applications, such as Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), Battery Management System (BMS) is needed to ensure battery safety and power delivery. BMS performs cell balancing (CB), State of Charge (SoC) estimation, monitoring, State of Health (SOH) estimation, and protective operation. To safeguard and optimize battery performance, required essential functionalities must be enabled. To optimize battery system performance, safety, and longevity, including temperature management, cell balancing, and communication protocols. This article provides an architecture that includes both a hardware demonstration and a simulation of the continuous on-time control approach for systematic measurement of Voltage, current, and temperature in EVs. A single-ended primary-inductance converter (SEPIC) DC-DC converter, Analogue Front End (AFE), and balancing circuits provide the optimal supply for proposed congregated BMS process. The effectiveness of proposed congregated design performance is validated through meter and sensor measurements for voltmeter, current, and temperature. The numerical error between proposed BMS and conventional measurements is relatively low for voltage (0.09 V), current (0.05 A), and temperature (0.09 °C). In the end, the simulated results and hardware results are benchmarked that the proposed congregated BMS design can regulate temperature, prevent overcharging and over-discharging, and balance the battery cells inside a given battery module.

Design of Electric Vehicle Battery Management System

The Battery Management System (BMS) is a fundamental component of electric vehicles, primarily utilized to ensure battery safety and enhance battery lifespan. This article presents a design for both the hardware and software components of the BMS, enabling battery monitoring and management. The hardware component encompasses the design of voltage acquisition circuitry, second-order filtering circuitry, sampling and holding circuitry, CAN bus communication circuitry, and other relevant features. The software section comprises subroutines for battery information collection, equalization circuitry, SOC estimation, and other relevant features. The BMS developed in this study successfully collects voltage, temperature, current, and other relevant information, and accurately estimates SOC and other crucial parameters. Testing confirmed that the battery management system precisely collects battery voltage, current, and temperature information, while the SOC estimation achieves a relatively high degree of accuracy.

Battery swapping and management system design for electric trucks considering battery degradation

Battery swapping and management system design for electric trucks considering battery degradation

Design and Analysis of Battery Management System for Electrical Vehicles

Abstract: The quantity of pollution that is emitted into the atmosphere will only continue to climb as the number of people who drive automobiles powered by internal combustion engines continues to rise. To reduce emissions of greenhouse gases, academics and companies on every continent are now focusing their attention on the research and development of more sophisticated technologies for electric cars. During this investigation, we are going to model and create a two-way power converter for electric automobiles. Batteries, a dc-dc converter, and a dc motor are just a few of the many diverse parts that make up the power electronics module. It is advised that the starting battery be charged to about 90% of its capacity before using the motor mode, which has a discharge current of 44.5 A. The battery stack has a maximum capacity of 100 ampere-hours, and its nominal voltage is 350 volts. This is the greatest amount of energy that it can store. Direct current (DC) machines have the potential to generate up to 250 horsepower, provided that the armature voltage is 500 volts and the field voltage is 300 volts, respectively. The mode of operation for the power converter is determined by the readings of torque that are obtained by the DC machine when it is operating in the motor mode and the generator mode, respectively. The processes of charging and discharging batteries have been monitored and handled in relation to the wide variety of modes of operation that may be found in DC machines. This was done in order to make full use of the capabilities of these machines. The bidirectional dc-dc converter, which may operate in either direction, is managed by a fuzzy logic controller. This allows the converter to work in either direction. It's likely that the converter and controller that's been shown here are all that's needed for charge management and running the motor in electric automobiles.

Comparison and Analysis of SOC Estimation Based on First-Order and Second-Order Thevenin Battery Models Based on EKF

The accurate modeling and estimation of state-of-charge (SOC) of lithium-ion batteries are of great significance for their utilization efficiency, service life extension and battery management system (BMS) design. This paper aims to provide understanding and guidance for understanding and guidance on different battery models and their parameter selection by comparing and analyzing the performance differences of Extended Kalman Filter (EKF) algorithm based on the first-order Thevenin battery model and the second-order Thevenin battery model. The Battery module in Matlab/Simulink is used to simulate the HPPC (HybridPulse Power Characterization) test of real batteries, and the model is parameterically identified. By establishing Thevenin battery models of different orders and applying the EKF algorithm for SOC estimation, the differences in accuracy, robustness and computational complexity of the two models are compared and analyzed, and experimental verification is carried out under different working conditions.

Estimation of State of Charge of Battery Used In Electric Vehicles With Wireless Battery Management System

This research paper presents a comprehensive investigation into the development and analysis of a wireless battery management system (BMS) using MATLAB Simulink. The primary objective of this study is to create an efficient, reliable, and scalable BMS that caters to the demands of various applications, such as electric vehicles, grid energy storage, and portable electronics. Our methodology involves designing and simulating key BMS components, including state estimation algorithms, fault detection mechanisms, and communication protocols, within the MATLAB Simulink environment. The paper first elucidates the motivation for adopting wireless technology in BMS, emphasizing its advantages over traditional wired systems. Subsequently, we explore the intricacies of the proposed wireless BMS architecture, detailing the implementation of essential features such as state-of-charge estimation, fault diagnosis, and thermal management. We also address the challenges associated with wireless communication, including latency, security, and energy efficiency, by incorporating robust communication protocols and power management strategies. Through rigorous simulations, we demonstrate the efficacy of the proposed wireless BMS, showcasing its ability to ensure optimal performance, safety, and longevity of battery packs. The outcomes of this research not only contribute to the advancement of BMS technology but also pave the way for further improvements in battery-powered systems. In conclusion, this paper offers a holistic perspective on wireless BMS design, emphasizing its potential to revolutionize energy management and extend the applications of battery technology in various domains.

Comparative Analysis of Charging and Discharging Characteristics for Batteries in Aircraft Electric Power Systems

Abstract—This paper presents a comparative analysis of the charging and discharging characteristics of batteries used in aircraft electric power systems. The performance and efficiency of different battery technologies play a crucial role in determining the viability of electric propulsion and power systems in aircraft applications. In this study, we systematically evaluate the charg- ing and discharging behaviors of various battery types, including LiFePO4, Ni-Cd, and lead acid, using Simulink. The simulations encompass state of charge (SOC) dynamics, charging efficiency, discharging profiles, and passive cell balancing technique. By utilizing Simulink, we can accurately model the behavior of different battery technologies under various operating conditions. The results obtained from the simulations provide valuable insights into the performance, efficiency, and overall suitability of battery technologies for aircraft electric power systems. This comparative analysis, serves as a valuable resource for engineers and researchers involved in the design and optimization of battery management systems for aircraft applications, aiding in the informed selection and integration of batteries in aircraft electric power systems. Index Terms—Charging Characteristics, Discharging Charac- teristics, Simulink Simulation, State of Charge (SOC), Passive Cell Balancing

13S Battery Pack and Battery Management System Design and Implementation for Electric Bicycles

In this study, the battery pack and ESP32 microcontroller-based battery management system (BMS) design for the electric bicycle have been carried out. The software updates were realized when the battery pack was in the box, thanks to the built-in Wi-Fi feature of the ESP32. The voltage values were read precisely, and a stable BMS was created with a 12-bit ADC-based ESP32 controller. The battery had temperature control from 7 different points. The temperature data was received from DS18B20 digital temperature sensors, and the charging current was cut off when the threshold value was exceeded. At the same time, the ACS712 5A current sensor was used to determine and prevent the excessive current draw. The charging current was defined as 2A. BMS cuts off the charging current to protect the battery pack when the charging current exceeds 3A. The resistor used for passive balancing in BMS was isolated from the ESP module with the KPS2801 optocoupler. The voltage of the battery pack was charged from 3.7 V to 3.85 V in the real-time test. The charging process continued for one hour, and the voltage changes of each cell were obtained in 10-minute periods. It was observed that all cells were charged in a balanced way at the end of the charging process. Thus, the charging process of the designed battery pack was carried out successfully through the designed BMS.

Lithium-ion ferrous phosphate prismatic cell aging analysis and assessment for the development of battery management systems

Electric off-road vehicles are gaining popularity as an alternative to fossil fuel-driven vehicles due to their efficiency and eco-friendliness. A series of numerical modelling and experimentation analysis is required to evaluate the trade-off between battery accuracy and life span to identify optimal battery management system design. In this study, investigations were carried out on a lithium-ion ferrous phosphate (LFP) prismatic cell in an electric-powered farm tiller application using the single particle model (SPM) method. The SPM method was used to analyse the battery's behaviour during charge–discharge profiles at 0.5, 1, and 2C ratings. By applying SPM discharging profiles, the Newman, Tiedemann, Gu, and Kim (NTGK) empirical analysis carried out cascaded thermal investigations. The NTGK and experimental studies showed a difference in the error of 0.23 %, 0.38 %, and 0.65 % for the 0.5, 1, and 2C ratings, respectively. Model order reduction (MOR) studies were performed to compute the heat generation rate in a prismatic cell comprising electrode pairs, separators, and current collectors. A parallel study of electrochemical impedance spectroscopy (EIS) experimentation was performed to evaluate the charge transfer resistance analysis for 500, 1000, and 1500 cyclic operations under different depths of discharge (DOD) conditions. The EIS studies assessed charge transfer resistance at maximum DOD conditions for the mentioned cyclic operations were found to be 135, 140, and 164 mΩ.

Parameter sensitivity analysis of an electrochemical-thermal model for energy-storage lithium-ion batteries

The lithium-ion batteries used for energy storage have the characteristics of large volume, high capacity, and long cycle life. Understanding the influence of physical parameters on electric potential and temperature is of critical importance for the design and operation of battery management systems. Here we developed an electrochemical-thermal coupled model that is composed of lithium-ion battery Pseudo-2D (P2D) model and heat transfer equations. A sensitivity analysis is carried out to illuminate the influence of various electrochemical parameters on battery capacity, terminal voltage, temperature curve and other technical indicators for a LiFePO4 battery with the capacity of 117Ah. The sensitivity matrices of the parameters under different C-rates and depth of discharge regions are organized, and a new five segments sensitivity analysis method is proposed in this study, which is helpful to reduce the sensitivity variance caused by the change of capacity during the discharging process. The parameters which have the greatest impact on battery capacity, voltage, and temperature are sorted out and illustrated. Furthermore, the influence rules of electrochemical parameters on the capacity and temperature-related technical indicators have also been summarized.

Design of Lithium Battery Management System of Hydrogen Emergency Vehicle

The hydrogen emergency power supply vehicle is mainly powered by a pure lithium battery power supply. Therefore, the reliable operation of the power supply and the analysis of charging characteristics play an important role. A battery management system for emergency vehicle power supply is designed in this paper. Through the battery management system, battery information collection, battery information analysis, and control management are carried out to realize the reliable operation of the power supply. The battery management system adopts the active equalization method for balance management, which improves the balance efficiency, improves the health status of the power supply, and extends the life of the power battery pack.