Approximations for Partial Differential Equations Appearing in Li-Ion Battery Models

2013 ◽  
Author(s):  
Nalin A. Chaturvedi ◽  
Jake F. Christensen ◽  
Reinhardt Klein ◽  
Aleksandar Kojic
Keyword(s):  
High Energy ◽  
High Energy Density ◽  
Particle Model ◽  
Approximation Technique ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Battery Model ◽  
Constant Diffusion ◽  
Li Ion

Li-ion based batteries are believed to be the most promising battery system for HEV/PHEV/EV applications due to their high energy density, lack of hysteresis and low self-discharge currents. However, designing a battery, along with its Battery Management System (BMS), that can guarantee safe and reliable operation, is a challenge since aging and other mechanisms involving optimal charge and discharge of the battery are not sufficiently well understood. In a previous article [1], we presented a model that has been studied in [2]–[5] to understand the operation of a Li-ion battery. In this article, we continue our work and present an approximation technique that can be applied to a generic battery model. These approximation method is based on projecting solutions to a Hilbert subspace formed by taking the span of an countably infinite set of basis functions. In this article, we apply this method to the key diffusion equation in the battery model, thus providing a fast approximation for the single particle model (SPM) for both variable and constant diffusion case.

On-chip Wide Range Bidirectional Current Sensor for Li-ion Battery Management System

2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Tzung-Je Lee ◽  
Yen-Ting Chen
Keyword(s):  
Driving Ability ◽  
Current Sensor ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Battery Model ◽  
Wide Range ◽  
Voltage Signal ◽  
Li Ion ◽  
On Chip

AbstractAn on-chip wide range bidirectional current sensor for monitoring Li-ion battery model 18650 is proposed in this paper. In order to detect the bidirectional current, two feedback sensing loops are employed. The feedback sensing loops generate differential sensed current signals. The output summation driver is included to convert the differential current signals to a single-ended output voltage signal and improve the driving ability. The proposed design is implemented using a typical 0.25

scholarly journals Estimation of State of Charge (SoC) Using Modified Coulomb Counting Method With Open Circuit Compensation For Battery Management System (BMS)

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Puspita Ningrum ◽  
Novie Ayub Windarko ◽  
Suhariningsih Suhariningsih
Keyword(s):  
Management System ◽  
Voltage Divider ◽  
Open Circuit ◽  
Voltage Sensor ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Control Center ◽  
Li Ion

Abstract— Battery is one of the important components in the development of renewable energy technology. This paper presents a method for estimating the State of Charge (SoC) for a 4Ah Li-ion battery. State of Charge (SoC) is the status of the capacity in the battery in the form of a percentage which makes it easier to monitor the battery during use. Coulomb calculations are widely used, but this method still contains errors during integration. In this paper, SoC measurement using Open Circuit Voltage Compensation is used for the determination of the initial SoC, so that the initial SoC reading is more precise, because if the initial SoC reading only uses a voltage sensor, the initial SoC reading is less precise which affects the next n second SoC reading. In this paper, we present a battery management system design or commonly known as BMS (Battery Management System) which focuses on the monitoring function. BMS uses a voltage sensor in the form of a voltage divider circuit and an ACS 712 current sensor to send information about the battery condition to the microcontroller as the control center. Besides, BMS is equipped with a protection relay to protect the battery. The estimation results of the 12volt 4Ah Li-ion battery SoC with the actual reading show an error of less than 1%.Keywords—Battery Management System, Modified Coulomb Counting, State of Charge.

scholarly journals Battery management system for Li-ion battery

2017 ◽  
Vol 2017 (13) ◽  
pp. 1437-1440 ◽  
Author(s):  
Fangfang Zhu ◽  
Guoan Liu ◽  
Cai Tao ◽  
Kangli Wang ◽  
Kai Jiang
Keyword(s):  
Management System ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Li Ion

scholarly journals Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1074 ◽  
Author(s):  
Yu Miao ◽  
Patrick Hynan ◽  
Annette von Jouanne ◽  
Alexandre Yokochi
Keyword(s):  
Electric Vehicles ◽  
Electrode Materials ◽  
Negative Electrode ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Li Ion ◽  
On The Road

Over the past several decades, the number of electric vehicles (EVs) has continued to increase. Projections estimate that worldwide, more than 125 million EVs will be on the road by 2030. At the heart of these advanced vehicles is the lithium-ion (Li-ion) battery which provides the required energy storage. This paper presents and compares key components of Li-ion batteries and describes associated battery management systems, as well as approaches to improve the overall battery efficiency, capacity, and lifespan. Material and thermal characteristics are identified as critical to battery performance. The positive and negative electrode materials, electrolytes and the physical implementation of Li-ion batteries are discussed. In addition, current research on novel high energy density batteries is presented, as well as opportunities to repurpose and recycle the batteries.

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