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 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.

scholarly journals Battery Balancing Algorithm for an Agricultural Drone Using a State-of-Charge-Based Fuzzy Controller

2020 ◽  
Vol 10 (15) ◽  
pp. 5277
Author(s):  
Sang-Bum Kim ◽  
Sang-Hyun Lee
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
State Of Charge ◽  
Battery Pack ◽  
Lithium Polymer Batteries ◽  
Active Balancing ◽  
Battery Packs ◽  
A Cell ◽  
Total Capacity ◽  
Cell Balancing

In this paper, we propose an intelligent battery control system that incorporates an active balancing technique and a fuzzy controller to manage and extend the life of an agricultural drone battery efficiently. The control system includes the following key features: A battery pack balancing algorithm based on a bidirectional DC/DC converter; a cell balancing system to prevent overcharge/discharge and ensure equal control of the cell voltages; and a monitoring system and wireless link to track the real-time status of the battery, temperature, and acceleration while the drone is in operation. Each battery pack consists of six lithium polymer batteries, one fuzzy controller per cell, and supports active balancing using the developed balancing technique. The capacity of each of the battery packs in the system is 11,000 mAh, and two can be combined to provide a total capacity of 22,000 mAh.

scholarly journals Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3532 ◽  
Author(s):  
Majid Astaneh ◽  
Jelena Andric ◽  
Lennart Löfdahl ◽  
Dario Maggiolo ◽  
Peter Stopp ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Battery Packs ◽  
Li Ion ◽  
Optimization Methodology ◽  
Battery Cells

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.

scholarly journals Hybrid Natural and Forced Active Balancing Control of Battery Packs State of Charge Based on Partnership for a New Generation of Vehicles

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Yewen Wei ◽  
Shuailong Dai ◽  
Jiayu Wang ◽  
Zhifei Shan ◽  
Jie Min
Keyword(s):  
Balance Control ◽  
Control Strategies ◽  
State Of Charge ◽  
Battery Pack ◽  
Obvious Effect ◽  
Active Balancing ◽  
Power Battery ◽  
Battery Packs ◽  
Natural Equilibrium ◽  
Balancing Control

Battery packs are widely used in electric vehicles, and their state-of-charge is one of the essential issues that affect the performances, whilst the balance between parallel and series cell of the battery pack always has an obvious effect. To enhance the working performance of the lithium-based power battery pack, a hybrid natural and forced active balancing control (HNFABC) strategy is proposed and adopted to the balancing circuit that is proposed in this work. These converters, which are advantageous in natural balancing and forced equalization, accelerate the balance speed of natural equilibrium in the final stage and protect the battery from being repeatedly charged and discharged. Simulation and experimental results show that HNFABC is not only simpler than other traditional balance control strategies but also faster in the equalization process. The idea of combining natural equilibrium and forced equilibrium can be inspired to be used in some related industries.

A Methodological Approach for Supporting the Thermal Design of Li-Ion Battery for Customized Electric Vehicles

2014 ◽  
Author(s):  
Daniele Landi ◽  
Paolo Cicconi ◽  
Michele Germani
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Thermal Design ◽  
Battery Pack ◽  
Scale Production ◽  
Li Ion Battery ◽  
Suitable Alternative ◽  
Li Ion

An important issue in the mechanical industry is the reduction of the time to market, in order to meet quickly the customer needs. This goal is very important for SMEs that produce small lots of customized products. In the context of greenhouse gas emissions reduction, vehicles powered by electric motors seem to be the most suitable alternative to the traditional internal combustion engine vehicles. The market of customized electric vehicles is a niche market suitable for SMEs. Nowadays, the energy storage system of an electric vehicle powertrain consists of several Li-ion cells arranged in a container called battery pack. Particularly, the battery unit is considered as the most critical component in electric vehicle, because it impacts on performance and life cycle cost. Currently, the design of a battery pack mostly depends on the related market size. A longer design time is expected in the case of a large scale production. While a small customized production requires more agility and velocity in the design process. The proposed research focuses on a design methodology to support the designer in the evaluation of the battery thermal behavior. This work has been applied in the context of a customized small production. As test case, an urban electric light commercial vehicle has been analyzed. The designed battery layout has been evaluated and simulated using virtual prototyping tools. A cooling configuration has been analyzed and then prototyped in a physical vehicle. The virtual thermal behavior of a Li-ion battery has been validated at the test bench. The real operational conditions have been analyzed reproducing several ECE-15 driving cycles and many acceleration runs at different load values. Thermocouples have measured the temperature values during the physical experiments, in order to validate the analytical thermal profile evaluated with the proposed design approach.

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.

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.

State-of-Charge Estimation of Li-Ion Battery in Electric Vehicles: A Deep Neural Network Approach

2020 ◽  
Vol 56 (5) ◽  
pp. 5565-5574
Author(s):  
Dickshon N. T. How ◽  
Mahammad A. Hannan ◽  
Molla S. Hossain Lipu ◽  
Khairul S. M. Sahari ◽  
Pin Jern Ker ◽  
...  
Keyword(s):  
Neural Network ◽  
Electric Vehicles ◽  
Deep Neural Network ◽  
State Of Charge ◽  
Li Ion Battery ◽  
Network Approach ◽  
Neural Network Approach ◽  
Li Ion ◽  
State Of Charge Estimation
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