energies-logo

Journal Browser

Journal Browser

Lithium Batteries for Vehicular Applications

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 13437

Special Issue Editor


E-Mail Website
Guest Editor
Department of Energy, Systems, Territory and Constructions, University of Pisa, 56122 Pisa, Italy
Interests: electric vehicles; railway systems; electrical power systems; electrochemical storage systems; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Lithium batteries in recent years have become a de-facto standard for installation on board electric and hybrid vehicles. However, manufacturers sometimes do not give all the needed information, and therefore it is not easy to select the proper lithium-based technology to be used. Additionally, batteries installed on board vehicles have a BMS (Battery Management System), which normally includes methods to correctly achieve battery SOC (State-Of-Charge) and SOH (State-Of-Health). Therefore, a numerical battery model with related algorithms is needed. This Special Issue seeks to address the lack of knowledge around these themes by inviting papers on experimental tests verification and design of algorithms specifically oriented to improve the use of batteries in vehicular applications.

Prof. Dr. Giovanni Lutzemberger
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Battery
  • model
  • State-Of-Charge
  • State-Of-Health
  • test

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

17 pages, 5547 KiB  
Article
A Systematic and Comparative Study of Distinct Recurrent Neural Networks for Lithium-Ion Battery State-of-Charge Estimation in Electric Vehicles
by Siyi Tao, Bo Jiang, Xuezhe Wei and Haifeng Dai
Energies 2023, 16(4), 2008; https://0-doi-org.brum.beds.ac.uk/10.3390/en16042008 - 17 Feb 2023
Cited by 3 | Viewed by 1581
Abstract
The precise estimation of the state of charge (SOC) is fundamental to the reliable operation of lithium-ion batteries. The development of deep learning techniques makes it possible to employ advanced methods to estimate a battery’s SOC. In order to better utilize a recurrent [...] Read more.
The precise estimation of the state of charge (SOC) is fundamental to the reliable operation of lithium-ion batteries. The development of deep learning techniques makes it possible to employ advanced methods to estimate a battery’s SOC. In order to better utilize a recurrent neural network (RNN) for battery SOC estimation, this paper conducts a comparative study of SOC estimation methods based on different RNN models. First, a general framework for deep-learning-based SOC estimation is undertaken, followed by the description of four kinds of RNNs employed in the estimation. Then, the estimation performances of these RNN models are compared under three scenarios, including the SOC estimation accuracy, the adaptability against different battery aging statuses, and the robustness against measurement uncertainties, in which the estimation performances of different RNN models are quantitively evaluated. Finally, a multiple-criteria decision-making method based on the analytic hierarchy process (AHP) is utilized to reflect the comprehensive performance of each RNN model, and the model with the highest score could be chosen for online SOC estimation during actual applications. This paper provides an in-depth analysis of RNN models in battery SOC estimation and could help battery management engineers develop the most appropriate estimation methods. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Figure 1

26 pages, 12569 KiB  
Article
Development and Experimental Validation of Novel Thevenin-Based Hysteretic Models for Li-Po Battery Packs Employed in Fixed-Wing UAVs
by Aleksander Suti, Gianpietro Di Rito and Giuseppe Mattei
Energies 2022, 15(23), 9249; https://0-doi-org.brum.beds.ac.uk/10.3390/en15239249 - 6 Dec 2022
Cited by 5 | Viewed by 1691
Abstract
Lithium batteries employed in lightweight fixed-wing UAVs are required to operate with large temperature variations and, especially for the emerging applications in hybrid propulsion systems, with relevant transient loads. The detailed dynamic modelling of battery packs is thus of paramount importance to verify [...] Read more.
Lithium batteries employed in lightweight fixed-wing UAVs are required to operate with large temperature variations and, especially for the emerging applications in hybrid propulsion systems, with relevant transient loads. The detailed dynamic modelling of battery packs is thus of paramount importance to verify the feasibility of innovative hybrid systems, as well as to support the design of battery management systems for safety/reliability enhancement. This paper deals with the development of a generalised approach for the dynamic modelling of battery packs via Thevenin circuits with modular hysteretic elements (open circuit voltage, internal resistance, RC grids). The model takes into account the parameters’ dependency on the state of charge, temperature, and both the amplitude and sign of the current load. As a relevant case study, the modelling approach is here applied to the Li-Po battery pack (1850 mAh, 6 cells, 22.2 V) employed in the lightweight fixed-wing UAV Rapier X-25 developed by Sky Eye Systems (Cascina, Italy). The procedure for parameter identification with experimental measurements, obtained at different temperatures and current loads, is firstly presented, and then the battery model is verified by simulating an entire Hybrid Pulse Power Characterisation test campaign. Finally, the model is used to evaluate the battery performance within the altitude (i.e., temperature) envelope of the reference UAV. The experiments demonstrate the relevant hysteretic behaviour of the characteristic relaxation times, and this phenomenon is here modelled by inserting Bouc–Wen hysteresis models on RC grid capacitances. The maximum relative error in the terminal output voltage of the battery is smaller than 1% for any value of state of charge greater than 10%. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Figure 1

15 pages, 5055 KiB  
Article
Gender Aspects in Driving Style and Its Impact on Battery Ageing
by Evelina Wikner, Raik Orbay, Sara Fogelström and Torbjörn Thiringer
Energies 2022, 15(18), 6791; https://0-doi-org.brum.beds.ac.uk/10.3390/en15186791 - 16 Sep 2022
Cited by 2 | Viewed by 1865
Abstract
The long and tiring discussion of who are the best drivers, men or women, is not answered in this article. This article, though, sheds some light on the actual differences that can be seen in how men and women drive. In this study, [...] Read more.
The long and tiring discussion of who are the best drivers, men or women, is not answered in this article. This article, though, sheds some light on the actual differences that can be seen in how men and women drive. In this study, GPS-recorded driving dynamics data from 123 drivers, 48 women and 75 men, are analysed and drivers are categorised as aggressive, normal or gentle. A total of 10% of the drivers was categorised as aggressive, with an even distribution between the genders. For the gentle drivers, 11% of the drivers, the men dominated. The driving style investigation was extended to utilise machine learning, confirming the results from statistical tools. As driving style highly impacts a vehicle’s fuel consumption, while switching over to battery electric vehicles it is important to investigate how the different driving styles impact battery utilisation. Two Li-ion battery cell types were tested utilising the same load cycle with three levels of current amplitude, to represent accelerations for the three drive categories. While one cell type was insensitive to the current amplitude, the highly energy-optimised cell proved to be sensitive to higher current amplitudes, corresponding to a more aggressive driving style. Thus, the amplitude of the dynamic current can for some cells be a factor that needs to be considered for lifetime predictions, while it can be neglected for other cells. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Graphical abstract

14 pages, 4369 KiB  
Article
An Electro-Thermal Model for LFP Cells: Calibration Procedure and Validation
by Michele Barbieri, Massimo Ceraolo, Giovanni Lutzemberger and Claudio Scarpelli
Energies 2022, 15(7), 2653; https://0-doi-org.brum.beds.ac.uk/10.3390/en15072653 - 5 Apr 2022
Cited by 6 | Viewed by 1804
Abstract
Lithium batteries for energy storage systems are a prominent solution for both stationary and mobile applications. Electro-thermal modelling of the cell is a useful tool for monitoring voltage and temperature in order to predict battery behaviour especially in cases of critical operative conditions. [...] Read more.
Lithium batteries for energy storage systems are a prominent solution for both stationary and mobile applications. Electro-thermal modelling of the cell is a useful tool for monitoring voltage and temperature in order to predict battery behaviour especially in cases of critical operative conditions. This paper provides a modelling approach focusing on the calibration of parameters of an electro-thermal model for large prismatic LFP lithium cells. The designed model is tuned by means of experimental tests that identify a set of parameters that are function of a cell’s state-of-charge and temperature. The model outputs are voltage, cell surface, and internal temperature profiles, which are validated against experimental data referring to realistic working conditions, even providing an intense level of thermal stress. The model accuracy is marked by a voltage mean average error lower than 1% and a mean cell surface temperature deviation lower than 1 K. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Figure 1

22 pages, 10896 KiB  
Article
Constitutive Behavior and Mechanical Failure of Internal Configuration in Prismatic Lithium-Ion Batteries under Mechanical Loading
by Zhijie Li, Jiqing Chen, Fengchong Lan and Yigang Li
Energies 2021, 14(5), 1219; https://0-doi-org.brum.beds.ac.uk/10.3390/en14051219 - 24 Feb 2021
Cited by 9 | Viewed by 2619
Abstract
Internal short circuits and thermal runaway in lithium-ion batteries (LIBs) are mainly caused by deformation-induced failures in their internal components. Understanding the mechanisms of mechanical failure in the internal materials is of much importance for the design of LIB pack safety. In this [...] Read more.
Internal short circuits and thermal runaway in lithium-ion batteries (LIBs) are mainly caused by deformation-induced failures in their internal components. Understanding the mechanisms of mechanical failure in the internal materials is of much importance for the design of LIB pack safety. In this work, the constitutive behaviors and deformation-induced failures of these component materials were tested and simulated. The stress-strain constitutive models of the anode/cathode and the separator under uniaxial tensile and compressive loads were proposed, and maximum tensile strain failure criteria were used to simulate the failure behaviors on these materials under the biaxial indentations. In order to understand the deformation failure mechanisms of ultrathin and multilayer materials within the prismatic cell, a mesoscale layer element model (LEM) with a separator-cathode-separator-anode structure was constructed. The deformation failure of LEM under spherical punches of different sizes was analyzed in detail, and the results were experimentally verified. Furthermore, the n-layer LEM stacked structure numerical model was constructed to calculate the progressive failure mechanisms of cathodes and anodes under punches. The results of test and simulation show the fracture failure of the cathodes under local indentation will trigger the failure of adjacent layers successively, and the internal short circuits are ultimately caused by separator failure owing to fractures and slips in the electrodes. The results improve the understanding of the failure behavior of the component materials in prismatic lithium-ion batteries, and provide some safety suggestions for the battery structure design in the future. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Figure 1

17 pages, 4775 KiB  
Article
Design of a Wireless Charging System for Online Battery Spectroscopy
by Edoardo Locorotondo, Fabio Corti, Luca Pugi, Lorenzo Berzi, Alberto Reatti and Giovanni Lutzemberger
Energies 2021, 14(1), 218; https://0-doi-org.brum.beds.ac.uk/10.3390/en14010218 - 4 Jan 2021
Cited by 35 | Viewed by 2970
Abstract
This paper presents the design procedure of an electric circuit that can perform the battery state diagnosis and, simultaneously, provide its charging. A fast and embedded impedance measurement method is also proposed; this is based on a broadband current signal excitation on the [...] Read more.
This paper presents the design procedure of an electric circuit that can perform the battery state diagnosis and, simultaneously, provide its charging. A fast and embedded impedance measurement method is also proposed; this is based on a broadband current signal excitation on the battery during the constant current charging phase. The proposed solution performs the electrochemical impedance spectroscopy (EIS), which is known to provide useful information about battery chemical–physical property changes due to aging or failure events. To demonstrate the functionalities of the proposed method, the spectroscopy is implemented in the control in the wireless charging system. An EIS charging test is simulated on an equivalent circuit model, which emulates the battery impedance properties in a specified frequency band. Circuit parameters are evaluated by experimental data. According to the obtained results, the proposed method allows us to reach an accurate estimation of the battery state and represents a promising solution for an embedded diagnostic of battery health thanks to its simplicity and speed. Full article
(This article belongs to the Special Issue Lithium Batteries for Vehicular Applications)
Show Figures

Figure 1

Back to TopTop