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 Electric Enabler

2017 ◽  
Vol 139 (12) ◽  
pp. 39-39
Author(s):  
John Kosowatz ◽  
Thomas Romer
Keyword(s):  
Production Process ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Automated System ◽  
Price Point ◽  
Battery Packs ◽  
Full Capacity ◽  
Safety Systems

This article explains how Tesla batteries are making electric vehicles (EVs) affordable for customers. Tesla’s battery revolution began when CEO Elon Musk declared that it would sell a mass-market EV for just $35,000. To produce battery packs cheaply enough to reach that price point, Tesla reengineered not only the production process, but also the factory in which the batteries are made. The Reno, Nev., Gigafactory is not yet operating at full capacity, but it is expected to produce 35 GW per year of lithium-ion batteries, about double the present-day global production. Tesla partnered with Panasonic to revamp the production process, and ended up redesigning the chemistry of the battery itself. The standard “18-650” cell format used thousands of less-expensive commodity cells, similar to lithium-ion batteries used in laptop computers. Tesla replaced individual safety systems built into each cell with an inexpensive fireproof system for the entire battery pack. Now, they have begun producing the new “2170” cell, which delivers higher density through an automated system developed with Panasonic to further reduce costs.

Lithium-Ion Battery Packs Formation With Improved Electrochemical Performance for Electric Vehicles: Experimental and Clustering Analysis

2019 ◽  
Vol 16 (2) ◽  
Author(s):  
Liu Yun ◽  
Jayne Sandoval ◽  
Jian Zhang ◽  
Liang Gao ◽  
Akhil Garg ◽  
...  
Keyword(s):  
Electrochemical Performance ◽  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Clustering Analysis ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Battery Pack ◽  
Self Organizing Map ◽  
Battery Packs

With the increase of production of electrical vehicles (EVs) and battery packs, lithium ion batteries inconsistency problem has drawn much attention. Lithium ion battery imbalance phenomenon exists during three different stages of life cycle. First stage is premanufacturing of battery pack i.e., during the design, the cells of similar performance need to be clustered to improve the performance of pack. Second is during the use of battery pack in EVs, batteries equalization is necessary. In the third stage, clustering of spent lithium ion batteries for reuse is also an important problem because of the great recycling challenge of lithium batteries. In this work, several clustering and equalization methods are compared and summarized for different stages. The methods are divided into the traditional methods and intelligent methods. The work also proposes experimental combined clustering analysis for new lithium-ion battery packs formation with improved electrochemical performance for electric vehicles. Experiments were conducted by dismantling of pack and measurement of capacity, voltage, and internal resistance data. Clustering analysis based on self-organizing map (SOM) neural networks is then applied on the measured data to form clusters of battery packs. The validation results conclude that the battery packs formed from the clustering analysis have higher electrochemical performance than randomly selected ones. In addition, a comprehensive discussion was carried out.

scholarly journals Adopting a Conversion Design Approach to Maximize the Energy Density of Battery Packs in Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1939
Author(s):  
Erika Pierri ◽  
Valentina Cirillo ◽  
Thomas Vietor ◽  
Marco Sorrentino
Keyword(s):  
Energy Density ◽  
Electric Vehicles ◽  
Design Procedure ◽  
Lithium Ion ◽  
High Energy ◽  
Battery Pack ◽  
High Energy Density ◽  
Installation Space ◽  
Battery Electric Vehicles ◽  
Battery Packs

Innovative vehicle concepts have been developed in the past years in the automotive sector, including alternative drive systems such as hybrid and battery electric vehicles, so as to meet the environmental targets and cope with the increasingly stringent emissions regulations. The preferred hybridizing technology is lithium-ion battery, thanks to its high energy density. The optimal integration of battery packs in the vehicle is a challenging task when designing e-mobility concepts. Therefore, this work proposes a conceptual design procedure aimed at optimizing the sizing of hybrid and battery electric vehicles. Particularly, the influence of the cell type, physical disposition and arrangement of the electrical devices is accounted for within a conversion design framework. The optimization is focused on the trade-off between the battery pack capacity and weight. After introducing the main features of electric traction systems and their challenges compared to conventional ones, the relevant design properties of electric vehicles are analyzed. A detailed strategy, encompassing the selection of battery format and technology, battery pack design and final assessment of the proposed set-up, is presented and implemented in an exemplary application, assuming an existing commercial vehicle as the reference starting layout. Prismatic, cylindrical and pouch cells are configured aiming at achieving installed battery energy as close as possible to the reference one, while meeting the original installation space constraint. The best resulting configuration, which also guarantees similar peak power performance of the reference battery-pack, allows reducing the mass of the storage system down to 70% of its starting value.

scholarly journals Task Planner for Robotic Disassembly of Electric Vehicle Battery Pack

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 387
Author(s):  
Martin Choux ◽  
Eduard Marti Bigorra ◽  
Ilya Tyapin
Keyword(s):  
Computer Vision ◽  
Electric Vehicles ◽  
Measurement Errors ◽  
Vision System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Computer Vision System ◽  
Electric Vehicle Battery ◽  
Robotic Disassembly ◽  
Total Average

The rapidly growing deployment of Electric Vehicles (EV) put strong demands on the development of Lithium-Ion Batteries (LIBs) but also into its dismantling process, a necessary step for circular economy. The aim of this study is therefore to develop an autonomous task planner for the dismantling of EV Lithium-Ion Battery pack to a module level through the design and implementation of a computer vision system. This research contributes to moving closer towards fully automated EV battery robotic dismantling, an inevitable step for a sustainable world transition to an electric economy. For the proposed task planner the main functions consist in identifying LIB components and their locations, in creating a feasible dismantling plan, and lastly in moving the robot to the detected dismantling positions. Results show that the proposed method has measurement errors lower than 5 mm. In addition, the system is able to perform all the steps in the order and with a total average time of 34 s. The computer vision, robotics and battery disassembly have been successfully unified, resulting in a designed and tested task planner well suited for product with large variations and uncertainties.

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.

Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles

Measurement ◽  
2019 ◽  
Vol 131 ◽  
pp. 443-451 ◽  
Author(s):  
Yujie Wang ◽  
Jiaqiang Tian ◽  
Zonghai Chen ◽  
Xingtao Liu
Keyword(s):  
Fault Diagnosis ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Model Based

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.

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