Online-Applicable Temperature Prediction Model for EV Battery Pack Thermal Management

2013 ◽  
Author(s):  
Tae Jin Kim ◽  
Byeng D. Youn ◽  
Hyun Jae Kim
Keyword(s):  
Prediction Model ◽  
Lithium Ion ◽  
Thermal Characterization ◽  
Operating Conditions ◽  
Battery Pack ◽  
Maintenance Cost ◽  
Thermal Monitoring ◽  
Temperature Prediction ◽  
Battery System ◽  
Customer Complaints

Lithium-ion (Li-ion) batteries may fail through thermal runaway caused by increased temperature. It is thus important to monitor battery temperature for prevention of the battery failure. Currently, thermal monitoring of the battery for electric vehicles (EVs) is being conducted by multiple thermostats. As the size of battery system increases and the cells are closely packed to exploit high power density, the number of thermostats is also increased to monitor the battery system. However, this increased number of sensors enhances the probability of the sensor malfunction, which prevents robust thermal monitoring, and causes increased maintenance cost and customer complaints. This paper thus proposes an online applicable temperature prediction model for EV battery pack while minimizing the number of sensors and keeping the monitoring capability. This was possible with three ideas: (a) devising battery thermal characterization test under various operating conditions, (b) development of the online-applicable temperature prediction model using artificial neural network (ANN), and (c) validation of the temperature prediction model. The proposed temperature prediction model was demonstrated with the EV battery pack that consists of twelve battery modules.

Energy Equalization Circuit with Multiple Primary Windings for Li-Ion Battery System

2013 ◽  
Vol 380-384 ◽  
pp. 3374-3377
Author(s):  
San Xing Chen ◽  
Ming Yu Gao ◽  
Guo Jin Ma ◽  
Zhi Wei He
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Battery System ◽  
Multiple Primary ◽  
In Series ◽  
A Cell ◽  
Li Ion ◽  
Number Of Cells

In this paper, a cell equalization circuit based on the Flyback topology is proposed for the Lithium-ion battery pack. Multiple transformers are employed in this circuit, equal to the number of cells in the pack. All the primary windings are coupled in series to provide the equalizing energy form the whole battery pack to the specific under charged cells. The structure and principle of the circuit is discussed, finally a prototype of four cells is presented to show the outstanding equalization efficiency of the proposed circuit.

scholarly journals Battery management system on electric bike using Lithium-Ion 18650

2019 ◽  
Vol 10 (3) ◽  
pp. 1529
Author(s):  
Soeprapto Soeprapto ◽  
Rini Nur Hasanah ◽  
Taufik Taufik
Keyword(s):  
Management System ◽  
Lithium Ion ◽  
Cell Voltage ◽  
Battery Pack ◽  
Maintenance Cost ◽  
Average Error ◽  
Battery Management System ◽  
Battery Management ◽  
The Individual ◽  
Electric Bike

<span>Electric bike (E-Bike) is a bicycle driven using an electric motor and uses batteries as the energy source. It is environmentally friendly as no exhaust gas is resulted during its operation. More than one battery is normally required, being arranged in series or in parallel connection. Over limit or overloaded conditions of battery usage will reduce the lifecycle of battery, speed up its replacement and add to the maintenance cost of electric bike. This paper proposes the prevention of such degrading condition using a tool to manage the battery usage both during the charging and discharging process. The proposed electronic Battery Management System (BMS) serves to regulate, monitor, and maintain the condition of batteries to prevent any possible damage. The resulted BMS design could provide a well balancing action in a battery system consisting of 13 cells utilizing the cell-to-cell active balancing method. The test results showed that the proposed BMS could monitor the individual cell voltage with an average error of 0.032 V (0.824</span><span lang="IN">%</span><span>), while reading the charge and discharge current with an average error of 0.04 A (</span><span lang="IN">6.25%</span><span>), and the battery pack temperature with an average error of 1.21<sup>o</sup>C (</span><span lang="IN">2.9%</span><span>). Additionally, the BMS could offer a functional battery pack protection system from conditions such as undervoltage, overvoltage, overheat, and overcurrent.</span>

scholarly journals Transient Temperature Distributions on Lithium-Ion Polymer SLI Battery

Vehicles ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 127-137 ◽  
Author(s):  
Yiqun Liu ◽  
Y. Gene Liao ◽  
Ming-Chia Lai
Keyword(s):  
Thermal Management ◽  
Thermal Model ◽  
Operating Temperature ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Battery Pack ◽  
Transient Temperature ◽  
Temperature Distributions ◽  
Lithium Ion Polymer Battery ◽  
Polymer Battery

Lithium-ion polymer batteries currently are the most popular vehicle onboard electric energy storage systems ranging from the 12 V/24 V starting, lighting, and ignition (SLI) battery to the high-voltage traction battery pack in hybrid and electric vehicles. The operating temperature has a significant impact on the performance, safety, and cycle lifetime of lithium-ion batteries. It is essential to quantify the heat generation and temperature distribution of a battery cell, module, and pack during different operating conditions. In this paper, the transient temperature distributions across a battery module consisting of four series-connected lithium-ion polymer battery cells are measured under various charging and discharging currents. A battery thermal model, correlated with the experimental data, is built in the module-level in the ANSYS/Fluent platform. This validated module thermal model is then extended to a pack thermal model which contains four parallel-connected modules. The temperature distributions on the battery pack model are simulated under 40 A, 60 A, and 80 A constant discharge currents. An air-cool thermal management system is integrated with the battery pack model to ensure the operating temperature and temperature gradient within the optimal range. This paper could provide thermal management design guideline for the lithium-ion polymer battery pack.

scholarly journals System-Level Modeling and Thermal Simulations of Large Battery Packs for Electric Trucks

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4796
Author(s):  
Anandh Ramesh Ramesh Babu ◽  
Jelena Andric ◽  
Blago Minovski ◽  
Simone Sebben
Keyword(s):  
Electric Vehicles ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Thermal Interface Material ◽  
Battery Pack ◽  
System Level ◽  
Modeling Framework ◽  
System Level Modeling ◽  
Battery Packs ◽  
Thermal Simulations

Electromobility has gained significance over recent years and the requirements on the performance and efficiency of electric vehicles are growing. Lithium-ion batteries are the primary source of energy in electric vehicles and their performance is highly dependent on the operating temperature. There is a compelling need to create a robust modeling framework to drive the design of vehicle batteries in the ever-competitive market. This paper presents a system-level modeling methodology for thermal simulations of large battery packs for electric trucks under real-world operating conditions. The battery pack was developed in GT-SUITE, where module-to-module discretization was performed to study the thermal behavior and temperature distribution within the pack. The heat generated from each module was estimated using Bernardi’s expression and the pack model was calibrated for thermal interface material properties under a heat-up test. The model evaluation was performed for four charging/discharging and cooling scenarios typical for truck operations. The results show that the model accurately predicts the average pack temperature, the outlet coolant temperature and the state of charge of the battery pack. The methodology developed can be integrated with the powertrain and passenger cabin cooling systems to study complete vehicle thermal management and/or analyze different battery design choices.

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 Empirical Thermal Performance Investigation of a Compact Lithium Ion Battery Module under Forced Convection Cooling

2020 ◽  
Vol 10 (11) ◽  
pp. 3732
Author(s):  
Akinlabi A. A. Hakeem ◽  
Davut Solyali
Keyword(s):  
Flow Rate ◽  
Thermal Performance ◽  
Air Flow ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Battery Pack ◽  
Performance Criteria ◽  
Maximum Temperature ◽  
Air Flow Rate ◽  
Worst Case

Lithium ion batteries (LiBs) are considered one of the most suitable power options for electric vehicle (EV) drivetrains, known for having low self-discharging properties which hence provide a long life-cycle operation. To obtain maximum power output from LiBs, it is necessary to critically monitor operating conditions which affect their performance and life span. This paper investigates the thermal performance of a battery thermal management system (BTMS) for a battery pack housing 100 NCR18650 lithium ion cells. Maximum cell temperature (Tmax) and maximum temperature difference (ΔTmax) between cells were the performance criteria for the battery pack. The battery pack is investigated for three levels of air flow rate combined with two current rate using a full factorial Design of Experiment (DoE) method. A worst case scenario of cell Tmax averaged at 36.1 °C was recorded during a 0.75 C charge experiment and 37.5 °C during a 0.75 C discharge under a 1.4 m/s flow rate. While a 54.28% reduction in ΔTmax between the cells was achieved by increasing the air flow rate in the 0.75 C charge experiment from 1.4 m/s to 3.4 m/s. Conclusively, increasing BTMS performance with increasing air flow rate was a common trend observed in the experimental data after analyzing various experiment results.

scholarly journals Dimensioning and Optimization of Hybrid Li-Ion Battery Systems for EVs

2018 ◽  
Vol 9 (2) ◽  
pp. 19 ◽  
Author(s):  
Jan Becker ◽  
Thomas Nemeth ◽  
Raphael Wegmann ◽  
Dirk Sauer
Keyword(s):  
Fixed Ratio ◽  
Lithium Ion ◽  
Maximum Power ◽  
Battery Pack ◽  
Optimization Approach ◽  
System Specification ◽  
Control Logic ◽  
Battery Cell ◽  
Battery System ◽  
Battery Systems

Commercial electric vehicles nowadays are powered by a battery system containing one kind of lithium-ion battery cell. Due to the fixed ratio of the cells’ maximum power to nominal energy, the possibilities for designing power and energy of the battery pack independently are limited. The battery system’s energy and maximum power can only be scaled by adapting the number of cells and modules, and the parameters furthermore depend on the characteristics of the cells used. Additional power electronics in the form of one or more dc/dc converters can be used to form a hybrid battery system comprised of more than one pack and different cell technologies. This allows for individually designing each battery pack and thus optimizing the overall battery system specification. This work presents a battery dimensioning and optimization approach for single pack and hybrid battery systems. It is based on an evolutionary optimization algorithm and a detailed, modular Matlab-Simulink vehicle model. Studies on the advantages of hybrid batteries for different vehicle classes were carried out. Results indicate that optimized hybrid battery systems can lead to weight and volume savings and further advantages in total cost of ownership, for example, by enhanced battery life time or reduced investment costs. On the other hand, they require more complex control logic, which is also discussed in this paper.

scholarly journals The parameter identification method study of the splice equivalent circuit model for the aerial lithium-ion battery pack

2018 ◽  
Vol 51 (5-6) ◽  
pp. 125-137 ◽  
Author(s):  
Shunli Wang ◽  
Carlos Fernandez ◽  
Xiaohan Liu ◽  
Jie Su ◽  
Yanxin Xie
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit ◽  
Experimental Studies ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Circuit Model ◽  
Operating Conditions ◽  
Battery Pack ◽  
Equivalent Model ◽  
Model Parameters

According to the special condition expression of the aerial lithium-ion battery pack, a novel targeted equivalent model (Splice–Equivalent Circuit Model) is proposed and constructed. The Splice–Equivalent Circuit Model achieves the accurate mathematical expression of the special operating conditions and the working process for the lithium-ion battery pack, which is realized by using the equivalent simulation of different internal effects in the charging and discharging process of the battery pack. The theoretical study and analysis of the working principle is investigated to express the working characteristics of the aerial lithium-ion battery pack together with the experimental analysis. Then, the equivalent circuit model of the aerial lithium-ion battery pack is carried out on the composite construction methods. The experimental studies are carried out in order to identify the parameters of the improved Splice–Equivalent Circuit Model, obtaining respectable identification results of battery equivalent model parameters.

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