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.

scholarly journals Environmental and Economic Benefits of a Battery Electric Vehicle Powertrain with a Zinc–Air Range Extender in the Transition to Electric Vehicles

Vehicles ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 398-412 ◽  
Author(s):  
Manh-Kien Tran ◽  
Steven Sherman ◽  
Ehsan Samadani ◽  
Reid Vrolyk ◽  
Derek Wong ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Combustion Engine ◽  
Global Climate ◽  
Storage System ◽  
Lithium Ion ◽  
Economic Benefits ◽  
Battery Pack ◽  
Range Extender ◽  
Transportation Sector ◽  
Li Ion

Emissions and pollution from the transportation sector due to the consumption of fossil fuels by conventional vehicles have been negatively affecting the global climate and public health. Electric vehicles (EVs) are a cleaner solution to reduce the emission and pollution caused by transportation. Lithium-ion (Li-ion) batteries are the main type of energy storage system used in EVs. The Li-ion battery pack must be considerably large to satisfy the requirement for the vehicle’s range, which also increases the cost of the vehicle. However, considering that most people use their vehicles for short-distance travel during daily commutes, the large pack is expensive, inefficient and unnecessary. In a previous paper, we proposed a novel EV powertrain design that incorporated the use of a zinc–air (Zn–air) battery pack as a range-extender, so that a smaller Li-ion pack could be used to save costs. The design and performance aspects of the powertrain were analyzed. In this study, the environmental and economic benefits of the proposed dual-battery powertrain are investigated. The results from the new powertrain were compared with values from a standard EV powertrain with one large Li-ion pack and a conventional internal combustion engine vehicle (ICEV) powertrain. In addition, an air pollution model is developed to determine the total amount of pollution released by the transportation sector on Highway 401 in Ontario, Canada. The model was then used to determine the effects of mass passenger EV rollout on pollution reduction.

Cell Balancing of Li-ion Battery Pack with Adaptive Generalised Extended State Observers for Electric Vehicle Applications

2021 ◽  
Author(s):  
Utkal Ranjan Muduli ◽  
Khaled Al Jaafari ◽  
Khalifa Al Hosani ◽  
Ranjan Kumar Behera ◽  
Rustem R. Khusnutdinov ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Extended State ◽  
State Observers ◽  
Li Ion ◽  
Cell Balancing

scholarly journals Li-Ion Battery Pack SoC Estimation for Electric Vehicles

2018 ◽  
Author(s):  
Kodjo Senou Rodolphe Mawonou ◽  
Akram Eddahech ◽  
Didier Dumur ◽  
Emmanuel Godoy ◽  
Dominique Beauvois ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Li Ion

Li-Ion Battery Pack Charging Process and Monitoring in Electric Vehicle

2014 ◽  
Vol 663 ◽  
pp. 504-509
Author(s):  
Yushaizad Yusof ◽  
Mohd Faiz Md. Adnan ◽  
Ralf Guenther ◽  
Mohd Hairi Mohd Zaman ◽  
Ahmad Asrul Ibrahim ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Battery Pack ◽  
Constant Current ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Voltage Level ◽  
Voltage Balancing ◽  
Li Ion ◽  
Charging And Discharging Processes

This paper presents the charging process procedure of Li-ion Battery pack for electric vehicle, which is implemented based on constant current and constant voltage (CC-CV) mode. All the informations regarding battery voltage level, state of charge (SOC) during charging and discharging processes, and battery temperature, is displayed on computer via battery management system (BMS). During the charging process, the BMS monitors the voltage balancing in Li-ion battery pack, as well as the cells voltage in each modules. The voltage difference between the highest voltage cell and the lowest voltage cell is very small, which validates the voltage stability and balance in battery pack during the charging and discharging processes.

A KBE Design Methodology to Support Li-Ion Battery Cooling for Hybrid and Electric Vehicles

2012 ◽  
Author(s):  
Daniele Landi ◽  
Paolo Cicconi ◽  
Michele Germani
Keyword(s):  
Electric Vehicles ◽  
Battery Pack ◽  
Electrochemical Reactions ◽  
Chemical Compositions ◽  
Main Question ◽  
Li Ion Battery ◽  
Knowledge Based ◽  
Medium Enterprise ◽  
Customized Production ◽  
Li Ion

In a scenario of a small and customized production of Electric Vehicles, it is important to have methodologies and tools able to guarantee high flexibility, good quality, and reduced time to market. The optimisation of electric motors and battery design stages is a key factor to achieve the expected results. Specific activities such as design automation, virtual prototyping and simulation are fundamental to obtain high-performance customised solutions. In this context the study of cooling systems for Li-Ion battery packs is one of the most important problems regarding EV and PHEV powertrain design. The proposed research presents a Knowledge Based methodology to support the cooling design of a battery pack and an analytical tool to evaluate the temperature and heat generation due to electrochemical reactions. All the research project is finalized to a definition of a Knowledge Based System to define a battery layout including engineering knowledge. The current strategies of battery pack design depend on the market size. In particular, the research activity is focalized on customized production of a SME (Small Medium Enterprise). The main question concerns the estimation of heat generated from electrochemical reactions in a single battery cell. In order to achieve these objectives, a preliminary phase for knowledge acquisition is necessary and a process of formalization has been carried out using the Knowledge Management methods. A first prototype of the Knowledge Based Engineering tool has been developed to determine the optimal cooling condition of a battery pack. The main module is based on an analytical approach which has been formulated to evaluate the average thermal flow generated by a standard LiFePO4 polymeric cell at different values of current and state of charge (SOC). This method can be used for different types of geometry and different chemical compositions. Finally, the proposed approach has been validated by experimental measures and numerical simulations in collaboration with a medium enterprise of electric energy storage systems and light ecological vehicles.

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.

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