scholarly journals A Cloud-based Aging Considered Vehicle-mounted Lithium-ion Battery Management Method: A Big Data Perspective

2019 ◽  
Author(s):  
Shuangqi Li ◽  
Hongwen He ◽  
Jianwei Li
Keyword(s):  
Big Data ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Battery Management ◽  
Management Method

scholarly journals A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2120 ◽  
Author(s):  
Wei He ◽  
Michael Pecht ◽  
David Flynn ◽  
Fateme Dinmohammadi
Keyword(s):  
Lithium Ion Battery ◽  
Solid Phase ◽  
Chemical Properties ◽  
Lithium Ion ◽  
State Of Charge ◽  
Critical Parameters ◽  
Estimation Accuracy ◽  
Moving Window ◽  
Battery Management ◽  
Electrochemical Model

State-of-charge (SOC) is one of the most critical parameters in battery management systems (BMSs). SOC is defined as the percentage of the remaining charge inside a battery to the full charge, and thus ranges from 0% to 100%. This percentage value provides important information to manufacturers about the performance of the battery and can help end-users identify when the battery must be recharged. Inaccurate estimation of the battery SOC may cause over-charge or over-discharge events with significant implications for system safety and reliability. Therefore, it is crucial to develop methods for improving the estimation accuracy of battery SOC. This paper presents an electrochemical model for lithium-ion battery SOC estimation involving the battery’s internal physical and chemical properties such as lithium concentrations. To solve the computationally complex solid-phase diffusion partial differential equations (PDEs) in the model, an efficient method based on projection with optimized basis functions is presented. Then, a novel moving-window filtering (MWF) algorithm is developed to improve the convergence rate of the state filters. The results show that the developed electrochemical model generates 20 times fewer equations compared with finite difference-based methods without losing accuracy. In addition, the proposed projection-based solution method is three times more efficient than the conventional state filtering methods such as Kalman filter.

scholarly journals Development of an Informative Lithium-Ion Battery Datasheet

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5434
Author(s):  
Weiping Diao ◽  
Chetan Kulkarni ◽  
Michael Pecht
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Battery Management

Lithium-ion battery datasheets, also known as specification sheets, are documents that battery manufacturers provide to define the battery’s function, operational limit, performance, reliability, safety, cautions, prohibitions, and warranty. Product manufacturers and customers rely on the datasheets for battery selection and battery management. However, battery datasheets often have ambiguous and, in many cases, misleading terminology and data. This paper reviews and evaluates the datasheets of 25 different lithium-ion battery types from eleven major battery manufacturers. Issues that customers may face are discussed, and recommendations for developing an informative and valuable datasheet that will help customers procure suitable batteries are presented.

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

Estimation of Remaining Useful Lifetime of Lithium-Ion Battery Based on Acoustic Emission Measurements

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Nejra Beganovic ◽  
Dirk Söffker
Keyword(s):  
Acoustic Emission ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Storage Device ◽  
Health State ◽  
Battery Management ◽  
Application Fields ◽  
Useful Lifetime

Lithium-ion battery (LIB) utilization as energy storage device in electric and hybrid-electric vehicles, wind turbine systems, a number of portable electrical devices, and in many other application fields is encouraged due to LIB small size alongside high energy density. Monitoring of LIB health state parameters, calculation of additional LIB operating parameters, and the fulfillment of safety requirements are provided through battery management systems. Prediction of remaining useful lifetime (RUL) of LIB and state-of-health (SoH) estimation are identified as still challenging and not completely solved tasks. In this contribution, previous works on RUL/SoH estimation, mainly relied on modeling of underlying electrochemical processes inside LIB, are compared with newly developed approach. The proposed approach utilizes acoustic emission measurements for LIB aging indicators estimation. Developed model for RUL estimation is closely related to frequency spectrum analysis of captured acoustic emission (AE) signal. Features selected from AE measurements are considered as model inputs. The novelty of this approach is the opportunity to estimate RUL/SoH of LIB without necessity to capture some intermediate variables, only indirectly related to RUL/SoH (charging/discharging currents, temperature, and similar). The proposed approach provides the possibility to obtain reliable information about current RUL/SoH without the knowledge about underlying physical processes occurred in LIB. Experimental data sets gathered from LIB aging tests are used for model establishment, training, and validation. The experimental results demonstrate the applicability of the novel approach.

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