scholarly journals A Novel Lithium Battery Equalization Circuit with Any Number of Inductors

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4764 ◽  
Author(s):  
Chusheng Lu ◽  
Longyun Kang ◽  
Xuan Luo ◽  
Jinqing Linghu ◽  
Hongye Lin
Keyword(s):  
Lithium Battery ◽  
Good Accuracy ◽  
Battery Pack ◽  
Voltage Level ◽  
Different Types ◽  
Battery Packs ◽  
Current Error

Even with the same voltage level, different types of battery packs have different requirements for the volume of the battery equalization circuit. However, most equalization circuits have the same problem: the volume of the equalization circuit is fixed once the voltage level of the battery pack is determined. In order to solve this problem, this paper proposes a novel lithium battery equalization circuit with any number of inductors (ECANI). It can select any number of inductors less than half the number of batteries, even when the voltage level of the battery pack is determined. Simulation and experiments are used to verify the performance of the equalization circuit. The current error and the average final voltage error in the experiment are 1.69% and 0.33% lower than those in the simulation, respectively. So the circuit can achieve equalization with good accuracy.

An Enhanced Active Balancing Circuit with Reconfigurable Battery for Electric Vehicles

2021 ◽  
Vol 23 (05) ◽  
pp. 762-775
Author(s):  
Gunalan K ◽  
◽  
Jesil Riba Bharathi A ◽  
Madhu Shree N ◽  
Ezhilarasi C ◽  
...  
Keyword(s):  
Life Span ◽  
Electric Vehicles ◽  
Vital Role ◽  
State Of Charge ◽  
Battery Pack ◽  
Voltage Level ◽  
Active Balancing ◽  
Electrical Vehicles ◽  
Battery Packs ◽  
Li Ion

Batteries play a vital role in Electrical Vehicles (EV). In a battery pack, voltage differences always exist due to charging and discharging cycles. It leads to an imbalance in the State of Charge (SoC) of Li-Ion battery packs. State of charge is the level of charge of an electric battery relative to its capacity. The voltage imbalances lead to the degradation of the cells by reducing their life span and usage time. Thus, a balancing circuit is necessary to maintain the same voltage level in all the cells. Also, a reconfiguration of the battery cells depending on their SoC levels and the requirement of the load can increase the usage time and life span of a battery pack. In this paper, a circuit for reconfiguration and active equalization is proposed based on a coupled inductor and switch network which can dynamically transfer charge from the cells with higher voltage to the ones with lower voltage while simultaneously delivering the load. Thus, the SoC of the cells can be balanced with an advantage of the coupled inductor ensuring faster equalization time than other balancing techniques.

scholarly journals Estimation of SOC Based on LSTM-RNN and Design of Intelligent Equalization Charging System

2020 ◽  
Vol 24 (7) ◽  
pp. 855-863
Author(s):  
Xi Chen ◽  
Kaoru Hirota ◽  
Yaping Dai ◽  
Zhiyang Jia ◽  
◽  
...  
Keyword(s):  
Lithium Battery ◽  
Single Cells ◽  
Current Source ◽  
Battery Pack ◽  
Constant Current ◽  
Series Data ◽  
Battery Management System ◽  
Constant Current Source ◽  
Charging System ◽  
Battery Packs

Lithium battery packs are the main driving energy source for electric vehicles. A battery pack equalization charging solution using a constant current source for variable rate charging is presented in this paper. The charging system consists of a main constant current source and independent auxiliary constant current sources. Auxiliary constant current sources are controlled by the battery management system (BMS), which can change the current rate of the corresponding single battery, and achieve full charging of each single cell in the series battery pack. At the same time, the state of charge (SOC) is regarded as time series data to establish a long short-term memory recurrent neural network (LSTM-RNN) model, and it is possible to obtain the single battery with lower capacity, so that the charging efficiency and battery pack consistency can be improved. The experimental results show that the open circuit voltage difference between the single cells is less than 50 mV after the charging of 20 strings of lithium battery packs by using this method, which achieve the purpose of equalization charging.

scholarly journals Estimation of the Hot Swap Circulation Current of a Multiple Parallel Lithium Battery System with an Artificial Neural Network Model

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1448
Author(s):  
Nam-Gyu Lim ◽  
Jae-Yeol Kim ◽  
Seongjun Lee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Lithium Battery ◽  
Battery Pack ◽  
Battery Management ◽  
Ann Model ◽  
Battery System ◽  
Load Current ◽  
Circulating Current ◽  
Artificial Neural

Battery applications, such as electric vehicles, electric propulsion ships, and energy storage systems, are developing rapidly, and battery management issues are gaining attention. In this application field, a battery system with a high capacity and high power in which numerous battery cells are connected in series and parallel is used. Therefore, research on a battery management system (BMS) to which various algorithms are applied for efficient use and safe operation of batteries is being conducted. In general, maintenance/replacement of multi-series/multiple parallel battery systems is only possible when there is no load current, or the entire system is shut down. However, if the circulating current generated by the voltage difference between the newly added battery and the existing battery pack is less than the allowable current of the system, the new battery can be connected while the system is running, which is called hot swapping. The circulating current generated during the hot-swap operation is determined by the battery’s state of charge (SOC), the parallel configuration of the battery system, temperature, aging, operating point, and differences in the load current. Therefore, since there is a limit to formulating a circulating current that changes in size according to these various conditions, this paper presents a circulating current estimation method, using an artificial neural network (ANN). The ANN model for estimating the hot-swap circulating current is designed for a 1S4P lithium battery pack system, consisting of one series and four parallel cells. The circulating current of the ANN model proposed in this paper is experimentally verified to be able to estimate the actual value within a 6% error range.

Self-Balancing by Design in Hybrid Electrochemical Battery Packs

2018 ◽  
Author(s):  
Nur Adilah Aljunid ◽  
Michelle A. K. Denlinger ◽  
Hosam K. Fathy
Keyword(s):  
Feedback Loop ◽  
Lithium Ion ◽  
Battery Pack ◽  
Hybrid Cells ◽  
Battery Cell ◽  
Battery Packs ◽  
Li Ion ◽  
Electrochemical Battery ◽  
Novel Concept ◽  
Physics Based Simulation

This paper explores the novel concept that a hybrid battery pack containing both lithium-ion (Li-ion) and vanadium redox flow (VRF) cells can self-balance automatically, by design. The proposed hybrid pack connects the Li-ion and VRF cells in parallel to form “hybrid cells”, then connects these hybrid cells into series strings. The basic idea is to exploit the recirculation and mixing of the VRF electrolytes to establish an internal feedback loop. This feedback loop attenuates state of charge (SOC) imbalances in both the VRF battery and the lithium-ion cells connected to it. This self-balancing occurs automatically, by design. This stands in sharp contrast to today’s battery pack balancing approaches, all of which require either (passive/active) power electronics or an external photovoltaic source to balance battery cell SOCs. The paper demonstrates this self-balancing property using a physics-based simulation of the proposed hybrid pack. To the best of the authors’ knowledge, this work represents the first report in the literature of self-balancing “by design” in electrochemical battery packs.

Repurposing of a Hybrid Vehicle Nickel Metal Hydride Battery Pack for Electrical Grid Storage

2017 ◽  
Author(s):  
Dayton Balderston ◽  
John Eric Kelley ◽  
James Crowder ◽  
Thomas DeAgostino ◽  
Christopher Depcik
Keyword(s):  
Control System ◽  
Metal Hydride ◽  
Battery Pack ◽  
Energy Output ◽  
Nickel Metal ◽  
Nickel Metal Hydride ◽  
Electrical Grid ◽  
Nickel Metal Hydride Battery ◽  
Battery Packs ◽  
Hydride Battery

Climate change concerns are driving incentives to increase the fuel economy of passenger vehicles. Consequently, this has resulted in a growing prevalence of electrified vehicles (EVs) consisting of hybrid, plug-in hybrid, and fully electric vehicles. Unfortunately, EVs are often removed from the road when 70 to 80% of the original energy capacity remains in their battery pack. In order to maintain or increase the value of EV battery packs in an end-of-vehicle life scenario, there are three potential solutions: remanufacturing for re-use, recycling, or repurposing. However, the complexity of handling dissimilar battery chemistries makes both remanufacturing and recycling a significant challenge. Hence, repurposing may prove to be a more viable short-term goal of the industry. In order to explore this potential outcome, a team of undergraduate students studied the continuous cycling effects of used and refurbished Toyota® Prius nickel metal hydride battery packs. A Raspberry Pi 2 Model B microcomputer recorded relevant data, including battery pack voltage, energy input, and energy output. In combination, a Laboratory Virtual Instrument Engineering Workbench (LabVIEW™) control system used this logged information to regulate charging and discharging of the battery pack. In addition, to enhance the environmental sustainability of the project, this control system acquired solar information from a nearby weather station, subsequently ensuring that the battery pack only recharged during times of peak solar radiation. Analysis of the pack’s energy balance helped to characterize the cycle life of the pack and its potential in repurposing. Others can emulate the methodology employed as a way to instruct students about the potential left in used vehicular battery packs and their possible integration with the electrical grid.

Thermal Management of Air-Cooling Lithium-Ion Battery Pack

2021 ◽  
Vol 38 (11) ◽  
pp. 118201
Author(s):  
Jianglong Du ◽  
Haolan Tao ◽  
Yuxin Chen ◽  
Xiaodong Yuan ◽  
Cheng Lian ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Thermal Management ◽  
Thermal Performance ◽  
Three Dimensional ◽  
Lithium Ion ◽  
Battery Pack ◽  
Cooling Effect ◽  
Air Cooling ◽  
Safety Issues ◽  
Battery Packs

Lithium-ion battery packs are made by many batteries, and the difficulty in heat transfer can cause many safety issues. It is important to evaluate thermal performance of a battery pack in designing process. Here, a multiscale method combining a pseudo-two-dimensional model of individual battery and three-dimensional computational fluid dynamics is employed to describe heat generation and transfer in a battery pack. The effect of battery arrangement on the thermal performance of battery packs is investigated. We discuss the air-cooling effect of the pack with four battery arrangements which include one square arrangement, one stagger arrangement and two trapezoid arrangements. In addition, the air-cooling strategy is studied by observing temperature distribution of the battery pack. It is found that the square arrangement is the structure with the best air-cooling effect, and the cooling effect is best when the cold air inlet is at the top of the battery pack. We hope that this work can provide theoretical guidance for thermal management of lithium-ion battery packs.

Internal Resistance Based Assessment Model for the Degradation of Li-Ion Battery Pack

2020 ◽  
Author(s):  
Iffandya Popy Wulandari ◽  
Min-Chun Pan
Keyword(s):  
Internal Resistance ◽  
Remaining Useful Life ◽  
Assessment Model ◽  
Battery Pack ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Battery Management System ◽  
Li Ion Battery ◽  
Battery Packs ◽  
Li Ion

Abstract As one pioneer means for energy storage, Li-ion battery packs have a complex and critical issue about degradation monitoring and remaining useful life estimation. It induces challenges on condition characterization of Li-ion battery packs such as internal resistance (IR). The IR is an essential parameter of a Li-ion battery pack, relating to the energy efficiency, power performance, degradation, and physical life of the li-ion battery pack. This study aims to obtain reliable IR through applying an evaluation test that acquires data such as voltage, current, and temperature provided by the battery management system (BMS). Additionally, this paper proposes an approach to predict the degradation of Li-ion battery pack using support vector regression (SVR) with RBF kernel. The modeling approach using the relationship between internal resistance, different SOC levels 20%–100%, and cycle at the beginning of life 1 cycle until cycle 500. The data-driven method is used here to achieve battery life prediction.based on internal resistance behavior in every period using supervised machine learning, SVR. Our experiment result shows that the internal resistance was increasing non-linear, approximately 0.24%, and it happened if the cycle rise until 500 cycles. Besides, using SVR algorithm, the quality of the fitting was evaluated using coefficient determination R2, and the score is 0.96. In the proposed modeling process of the battery pack, the value of MSE is 0.000035.

scholarly journals Scheduled Pre-Heating of Li-Ion Battery Packs for Balanced Temperature and State-of-Charge Distribution

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2212
Author(s):  
Hien Vu ◽  
Donghwa Shin
Keyword(s):  
Thermal Characteristics ◽  
Lithium Ion ◽  
State Of Charge ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Internal Heating ◽  
Heating Efficiency ◽  
Battery Packs ◽  
Unit Cells ◽  
Li Ion

Lithium-ion batteries exhibit significant performance degradation such as power/energy capacity loss and life cycle reduction in low-temperature conditions. Hence, the Li-ion battery pack is heated before usage to enhance its performance and lifetime. Recently, many internal heating methods have been proposed to provide fast and efficient pre-heating. However, the proposed methods only consider a combination of unit cells while the internal heating should be implemented for multiple groups within a battery pack. In this study, we investigated the possibility of timing control to simultaneously obtain balanced temperature and state of charge (SOC) between each cell by considering geometrical and thermal characteristics of the battery pack. The proposed method schedules the order and timing of the charge/discharge period for geometrical groups in a battery pack during internal pre-heating. We performed a pack-level simulation with realistic electro-thermal parameters of the unit battery cells by using the mutual pulse heating strategy for multi-layer geometry to acquire the highest heating efficiency. The simulation results for heating from −30 ∘ C to 10 ∘ C indicated that a balanced temperature-SOC status can be achieved via the proposed method. The temperature difference can be decreased to 0.38 ∘ C and 0.19% of the SOC difference in a heating range of 40 ∘ C with only a maximum SOC loss of 2.71% at the end of pre-heating.

Sign in / Sign up

Export Citation Format

Share Document