Lithium Battery Management Research Articles

Development of an Inertial Measurement Unit (IMU) with datalogger and geopositioning for mapping the Earth’s magnetic field

The Earth’s magnetic field is used in various navigation systems, but this field has a dynamic behavior that can be affected by different physical factors in local environments. These factors can pose risks to navigation systems and at the same time be a signal of a phenomenon that needs to be investigated, such as mineral concentration or the presence of interference from electrical equipment, among others. For that reason, in this project, this system was designed and integrated using a low-cost, military-grade magnet inductive magnetometer, which is integrated into two Inertial Measurement Units to corroborate the movement data, and at the same time a geopositioning system to georeference the sensor measurements. The information is managed by an MCU, which also stores data on an SD card. The system includes a lithium battery management system to provide more than an hour of autonomy. Wireless communication systems are intentionally avoided to prevent interference, and an infrared transmission LED is included instead, in case the real-time transmission is necessary. The results show that the proposed system allows for obtaining maps of magnetic field intensity in open spaces, and this information can be used to determine regions with anomalies.

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.

State of Charge Estimation and Evaluation of Lithium Battery Using Kalman Filter Algorithms.

The accurate and rapid estimation of the state of charge (SOC) is important and difficult in lithium battery management systems. In this paper, an adaptive infinite Kalman filter (AUKF) was used to estimate the state of charge for a 18650 LiNiMnCoO2/graphite lithium-ion battery, and its performance was systematically evaluated under large initial errors, wide temperature ranges, and different drive cycles. In addition, three other Kalman filter algorithms on the predicted SOC of LIB were compared under different work conditions, and the accuracy and convergence time of different models were compared. The results showed that the convergence time of the AUKF algorithms was one order of magnitude smaller than that of the other three methods, and the mean absolute error was only less than 50% of the other methods. The present work can be used to help other researchers select an appropriate strategy for the SOC online estimation of lithium-ion cells under different applicable conditions.

A novel hybrid data-driven method based on uncertainty quantification to predict the remaining useful life of lithium battery

Accurate future capacity and remaining useful life (RUL) prediction of lithium battery, as well as uncertainty quantification, are critical for lithium battery management system. A hybrid data-driven method is utilized in this research. Firstly, using complementary ensemble empirical mode decomposition and Hurst exponent-based data refactoring method, raw capacity data is split into two local fluctuation components with various time scales and one component with long-term memory feature. Then, Gaussian process regression (GPR) is utilized to predict the two local fluctuation components, and long short-term memory (LSTM) neural network is utilized to predict the long-term memory feature component, while the prediction error and its uncertainty quantification are given by using GPR learning training error. Finally, all results are combined into the future capacity prediction value and its 95% confidence interval. Applying multiple datasets of lithium battery capacity degradation, the proposed method is compared to others. The experimental results reveal that the proposed method outperforms the other methods in the future capacity prediction, with root mean squared error (RMSE) and mean absolute error (MAE) of 0.01057 and 0.00659. Furthermore, when RUL prediction is conducted early in the cycle, the proposed method has strong generalization ability and trustworthy uncertainty management capacity.

Collaborative state estimation of lithium‐ion battery based on multi‐time scale low‐pass filter forgetting factor recursive least squares ‐ double extended Kalman filtering algorithm

AbstractFor the lithium battery management system and real‐time safety monitoring, two issues are of great significance, namely, the ability to accurately update the model parameters in real time and to accurately estimate the state of charge and health. In this context, this thesis adopts the second‐order RC equivalent circuit model and the forgetting factor recursive least squares ‐ double extended Kalman filtering (FFRLS‐DEKF) algorithm with multi‐time scales and low‐pass filter. Forgetting factor recursive least squares is applied to conduct online parameter identification, and the traditional double extended Kalman filtering algorithm is optimized to evaluate the state of charge and model parameters in the micro‐scale and macro‐scale. In this way, the error caused by two different characteristics is reduced, and a low‐pass filter is added to optimize the fluctuation problem of the estimated value of the model parameters. According to the experiment results, the maximum error between the model simulation value and the actual value of the terminal voltage is 0.0459 V. If the initial value of the state of charge deviates from the actual value, the maximum errors under BBDST and HPPC conditions record 0.0235 and 0.0048, respectively, the forgetting factor recursive least squares ‐ double extended Kalman filtering algorithm with multi‐time scales and low‐pass filter is able to track the true value within 40 s. Furthermore, the lithium‐ion battery state of health both reaches 98% under the two conditions. In summary, the experimental analysis shows that the algorithm helps reduce the influence of initial values on the results, thereby reducing error accumulation and improving the robustness.

Design of power lithium battery management system based on digital twin

The accurate estimation of the State of Charge (SoC) of batteries has always been the focus of Battery Management System (BMS). However, the current BMS has problems such as difficult data sharing, weak data processing capability and limited data storage capacity, so the simplest ampere-time integration method is used to estimate the SoC, and the estimation results are highly biased. In this paper, an innovative digital twin-driven battery system framework is proposed and successfully developed. A joint HIF-PF online algorithm for estimating SoC under the experimental condition Beijing Bus Dynamic Stress Test (BBDST) is also proposed, which is comparable to the conventional Extended kalman filter (EKF), HIF and Particle Filter (PF). The results demonstrate the superiority of the algorithm. Then, we applied the algorithm to estimate SoC. In addition, the system implements functions such as real-time voltage and current monitoring and visualization.

Research on Lithium Battery Management System for Electric Trackless Rubber Tyred Vehicle in Coal Mine

This paper designs a kind of lithium battery management system for coal mine electric trackless rubber tyred vehicle based on chip STM32F105VCT7 as CPU. It focuses on the battery grouping mode, battery balancing strategy and the hardware and software design of the battery management system. The lithium battery management system uses LTC6811-1 chip to collect battery information, designs passive balance to maintain the battery, and uses RT thread real-time operating system to schedule the tasks in the lithium battery management system. Through the actual test application, the lithium battery management system designed in this paper can effectively monitor the battery voltage, temperature, current and other information, and complete the battery balance, charge and discharge control.

Research on Test Platform of Lithium Battery Management System based on LabVIEW

With the application and popularization of new energy electric vehicles, the research and design of lithium battery management system is of great practical significance to ensure the normal operation of battery pack and vehicle safety, and improve vehicle performance. This paper first analyzes the design of the lithium battery management system, then designs the upper computer control system, and finally verifies the effectiveness of the lithium battery thermal management system through the system test.

Research on High Precision Lithium Battery Management System

Lithium battery has been used more and more in recent years due to its excellent performance such as high energy, high voltage, long service life, low self-discharge rate, environmental protection and so on. However, lithium battery also has the disadvantages of poor safety performance, complex protection circuit, high cost, etc. The high-precision lithium ion battery management system (BMS) is proposed to solve the charging and discharging protection problem of multiple lithium batteries. In order to solve this problem, we have designed a set of high-precision lithium battery management system by pulse width modulation based on previous studies.

Harvesting thermoelectric energy from railway track

This study aims to develop a prototype for harvesting thermoelectric energy from railway track. By capturing the existing thermal energy in railway tracks, this technology helps power rail-side sensors in off-grid and remote areas without depleting natural resources. In low latitudes such as southern China, the temperature of railway tracks can reach 57 °C due to solar radiation. However, at a relatively shallow depth (200 mm), the substratum below the track foundation (e.g., soils) has a lower temperature (i.e., 15 °C–26 °C). This temperature difference can be used to generate electricity through a thermoelectric generator (TEG). The proposed approach captures thermal energy from the railway track and transfers the energy to the TEG prototype beneath the bottom of rails. Evaluation of the prototype is conducted by finite volume analysis, field test, and laboratory experiment. The results indicate that the TEG prototype can produce 5.8 mW–316.8 mW of power across a resistant load at thermal gradient from 8 °C to 29.2 °C. A DC-DC buck-booster circuit with lithium battery management is developed to charge the batteries by the harvested thermal energy. The system operates at a low startup voltage of 0.9 V and its conversion efficiency is larger than 60%.

Modeling and SOC estimation of lithium iron phosphate battery considering capacity loss

Modeling and state of charge (SOC) estimation of Lithium cells are crucial techniques of the lithium battery management system. The modeling is extremely complicated as the operating status of lithium battery is affected by temperature, current, cycle number, discharge depth and other factors. This paper studies the modeling of lithium iron phosphate battery based on the Thevenin’s equivalent circuit and a method to identify the open circuit voltage, resistance and capacitance in the model is proposed. To improve the accuracy of the lithium battery model, a capacity estimation algorithm considering the capacity loss during the battery’s life cycle. In addition, this paper solves the SOC estimation issue of the lithium battery caused by the uncertain noise using the extended Kalman filtering (EKF) algorithm. A simulation model of actual lithium batteries is designed in Matlab/Simulink and the simulation results verify the accuracy of the model under different operating modes.

The master control software for power lithium battery management system based on MCS D2P development platform

The master control software for power lithium battery management system based on MCS D2P development platform

Design and Research of Power Lithium Battery Management System

Due to the problems of overcharge, over discharge, internal and external short circuit and thermal runaway in the use of lithium battery, a low-power lithium battery management system was designed for these problems. This system takes MSP430 as the core, using BQ76925 chip of TI company as the front-end acquisition chip can detect 3 to 6 string lithium battery with voltage, current, temperature and other information collection, overcharge and over discharge protection, balance management and other functions. The test shows that the system is good for the management of lithium battery and has good accuracy and stability.

Research on the management system of lithium battary

Lithium battery is the first choice for the energy source of explosion-proof electrical equipment because of its small size, light weight and large energy. In order to ensure the safety, improve the battery life and prolong the service life of the lithium battery, it is necessary to study the lithium battery management system. For this reason, the article uses the modular design idea to design a lithium battery intelligent management system. The system takes the microcontroller as the core to control the current voltage signal sampling, power indicator, serial communication and other management functions, and combined with the software process, the implementation of the system control algorithm is described in detail. Finally, combined with the system software and hardware function, and through repeated experiments and continuous improvement and improvement, it can be run safely and stably.

Development of Power Supply Management Module for Radio Signal Repeaters of Automatic Metering Reading System in Variable Solar Density Conditions

Abstract In recent years, there has been significant research focus that revolves around harvesting and minimising energy consumption by wireless sensor network nodes. When a sensor node is depleted of energy, it becomes unresponsive and disconnected from the network that can significantly influence the performance of the whole network. The purpose of the present research is to create a power supply management module in order to provide stable operating voltage for autonomous operations of radio signal repeaters, sensors or gateways of WSN. The developed management module is composed of a solar panel, lithium battery and power supply management module. The novelty of the research is the management module, which ensures stable and uninterrupted operations of electronic equipment in various power supply modes in different situations, simultaneously ensuring energy protection and sustainability of the module components. The management module is able to provide power supply of 5 V for electronics scheme independently, without power interruption switching between power sources and power flows in different directions.

A Viability Study of a Lithium Battery Powered Golf Cart

AbstractThere is a recent trend among low speed electric vehicle manufacturers to update traction batteries from older, heavy chemistries to new, lighter battery chemistries. In this viability study, a Club Car Villager LSV electric golf cart was converted from the original flooded lead acid batteries to hard carbon/mixed oxide lithium batteries. The range and speed of both chemistries are compared. This paper demonstrates a potential operational savings for ight electric vehicle users. Despite a reduction in volume, the lithium batteries outperformed the lead acid in both range (46.7% increase) and charging time (95% reduction). The range increase was due, in part, to a reduction in battery weight of 62.5%. In addition to range test results, implementation of the lithium battery management system and J1772 charger system used to support this conversion are discussed.

An improved charging/discharging strategy of lithium batteries considering depreciation cost in day-ahead microgrid scheduling

An energy storage system is critical for the safe and stable operation of a microgrid (MG) and has a promising prospect in future power system. Economical and safe operation of storage system is of great significance to MGs. This paper presents an improved management strategy for lithium battery storage by establishing a battery depreciation cost model and employing a practical charging/discharging strategy. Firstly, experimental data of lithium battery cycle lives, which are functions of the depth of discharge, are investigated and synthesized. A quantitative depreciation cost model is put forward for lithium batteries from the perspective of cycle life. Secondly, a practical charging/discharging strategy is applied to the lithium battery management in MGs. Then, an optimal scheduling model is developed to minimize MG operational cost including battery depreciation cost. Finally, numerical tests are conducted on a typical grid-connected MG. Results show that the depth of discharge of storage is scheduled more rationally, and operational cost is simultaneously saved for MG under the proposed management strategy. This study helps to improve the cost efficiency and alleviate the aging process for lithium batteries.

소형 전기에너지저장장치 운전조건에 따른 방사 및 전도 방해에 관한 연구

When using a secondary battery in energy storage units, if the grid is in light duty the active power is stored so it can be used when the grid is in heavy duty. This makes possible for the load equalize and make the grid optimized. Recently the government is trying to propagate this technology. Depending on its capacity this kind of electric energy storage unit is used in adjusting the frequency, break up the energy peak in summer and winter, stabilize the energy output of renewable energy which can change unstably because of the environment. Which makes it possible to stabilize the grid. It is anticipated that market of 120 trillion won will be developed worldwide in 2030. Currently in Korea a steady supply is in progress. However because of stray electromagnetic waves some other electronics are malfunctioning. This paper covers the research in the method to detect the emission noise in small electric energy storage units using lithium secondary batteries and battery management system, Power conditioning systems with CIPSR standards. And the research of a more efficient method to measure such stray electromagnetic waves.

Research and Design on Lithium Battery Management System in Communication Equipment

As a communication system power, the lithium battery would be the trend of industry in the wake of development in battery technology. Communication systems have special requirement for lithium battery like low power consumption, high stability and data remote visibility. In this paper, a new type of lithium batteries management system is designed to fit the application of lithium batteries in the communication industry.

Research on a New Type of Lithium Battery String Equalization and Management System

Lithium battery has been employed widely in many industrial applications. Parameter mismatches between lithium batteries along a series string is the critical limits of the large-scale applications in high power situation. Maintaining equalization between batteries is the key technique in lithium batteries application. This paper summarizes normal equalization techniques and proposed a new type of lithium Battery Equalization and Management System (BEMS) employing the isolated DC-DC converter structure. The system is integrated both equalization functions and management functions by using distributed 3-level controlled structure and digital control technique. With this control method the flexibility of the balance control strategy and the compatibility for different battery strings are both improved dramatically. The experimental results show optimizing equalization, efficiency and the battery string life span has been extended.