Automotive Science and Engineering

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In the present study, a model of a large Lithium Polymer (Li-Po) battery for use in the simulation of Hybrid Electric Vehicles (HEVs) is developed. To attain this goal, an Equivalent Circuit (EC) consisting of a series resistor and two RC parallel networks is considered. The accuracy and the response time of the model for use in an HEV simulator are studied. The battery parameters identification and model validation tests are performed in low current with a good accuracy. Similar test process is implemented in high current for another cell and the simulation is verified with experimental results. The validation tests confirm the accuracy of the model for use in HEV simulator. Finally, the battery model is used to model a Vehicle, Fuel and Environment Research Institute (VFERI) hybrid electric city bus using ADVISOR software and its compatibility with other components of the vehicle simulator are demonstrated in a drive cycle test.

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This paper mainly discusses the thermal behavior and performance of Lithium-ion batteries utilized in hybrid electric vehicles (HEVs), battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) based on numerical simulations. In this work, the battery’s thermal behavior is investigated at different C-rates and also contour plots of phase potential for both tabs and volume-monitored plot of maximum temperature inside the computational domain is illustrated. The numerical simulation is done via ANSYS Fluent traditional software package which utilizes the dual potential multi-scale multi-dimensional (MSMD) battery model to analyze the cell discharge behavior and investigate the thermal performance and potential variation(s). The results show that the maximum temperature of battery surface is proportional to the battery discharge rate, i.e., the higher the C-rate, the greater cell surface temperature. Moreover, an increasing symmetric pattern is noticed for volume monitor of maximum temperature over the simulation period. Finally, it is worth noting that the battery tab potential varies more quickly if the C-rate becomes greater. In fact, the lowest and highest rate of changes are observed for 1C and 4C, respectively.

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With respect to the limitations of fossil energy resources, different types of electric vehicles (EVs) are developed as suitable alternatives. Lithium-ion (Li-ion) battery cells play an extremely important role in EVs due to their unique features. But they need a thermal management system (TMS) to maintain their surface temperature uniformity and avoid them from thermal runaways. In the current study a phase change material (PCM) based TMS is introduced and applied to provide a uniform temperature distribution on a Li-ion battery cell surface. This PCM based TMS declines the final maximum temperature difference to (1/5) and (2/3) at 1 C and 2 C discharge rate respectively.
 

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This paper investigates the effect of temperature on a hybrid energy storage system with various energy management systems. The hybrid energy storage system consists of a fuel cell, ultracapacitor and battery with associated DC/DC and DC/AC converters. The energy management strategies employed are the state machine control strategy, fuzzy frequency/logic decoupling strategy, minimization strategy of equivalent consumption (ECMS) and external energy maximization strategy (EEMS). Initially, a module of 3.3v 2.3Ah LiPo4 batteries consisting of 15 cells in series and 15 rows in parallel are studied without considering the temperature effect. In the next step, the studies are repeated considering the temperature variation effects. The current and SOC associated with the battery, the hydrogen consumption, and battery life are studied for each strategy. The results suggest that the errors associated with the battery life estimation, as well as the battery current are significant with and without considering the temperature effects with the values of 30% and 20%, respectively.

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In recent years, the automotive industry has experienced a dramatic mutation in the develop ment of electric vehicles. One of the most important aspects of this type of vehicle is its thermal management. Among the various parts of an electric vehicle that are subjected to thermal management, the battery is of particular importance. Battery cell temperatures may exceed the allowable range due to continuous and high-pressure operation and various weather conditions, and this, in addition to performance, severely affects battery life. Therefore, the appropriate cooling system is essential. In this research, the most common methods of battery cooling are investigated. First, three-dimensional thermal analysis on the battery is performed using the computational fluid dynamics method in transient and steady-state phases.  Then, the effect of changing the cooling flow rate on the maximum temperature of the battery cell as well as the temperature difference of the cells in the battery pack is investigated. The effect of changing inlet coolant temperature change on battery cell temperature distribution is also investigated. The results show that by increasing the flow rate from 0.5 to 1.2 liter per minute, the maximum temperature in the battery pack and the temperature difference between the cells decrease to 44.4 and 2.51 ° C, respectively. Also, by changing the temperature of the inlet coolant from 15 to 30 ° C, the maximum temperature in the battery pack increases up to 42.2 ° C and the temperature difference is negligible.

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As electric vehicles become more popular, we need to keep improving the lithium-ion batteries that power them. Electrochemical impedance spectroscopy (EIS) is used based on a discrete random binary sequence (DRBS) to reduce excitation time in the low-frequency region and excite the input of the battery. In this paper, voltage and current signals are processed with wavelet transform for impedance evaluation. In using wavelet transform, choosing the most optimal mother wavelet is crucial for impedance evaluation since different mother wavelets can produce different results. We aim to compare three types of continuous Morse mother wavelet, continuous Morlet, and continuous lognormal wavelet, which are among the most important mother wavelets, to determine the best method for impedance evaluation. We used the dynamic time-warping algorithm to quantify the difference between the initial values obtained from standard laboratory equipment and the impedance evaluation through three different continuous wavelets. Our proposed method (lognormal wavelet) has the lowest difference (3.4086) from the initial values compared to the Morlet (3.5504), and Morse (3.5457) methods. As a result, our simulation shows that the lognormal wavelet transform is the best method for impedance evaluation compared to Morlet and Morse wavelets.

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The hydrogen fuel cell is one of the latest technologies used in fuel cell electric vehicles (FCEVs), which uses hydrogen gas to supply the electrical energy needed by the electric engines. The proposed topology has boost function and uses a novel diodes and switches network, which leads to the creation of an integrated system with high efficiency and high voltage gain. Other advantages of the proposed converter are small size, low voltage and current stresses on all the components, less component count, continuous input current and light weight; which makes it more efficient compared to existing structures. In this regard, theoretical calculations and steady state analysis for the proposed system have been presented. Also, in order to verify the performance of the proposed converter, it has been simulated in the MATLAB/Simulink software environment at the rated power of 1kW, with an output voltage of 220V and an output current of 4.55A, and the results have been presented in detail. The peak efficiency of the proposed converter reached 97.4% at half power, and the efficiency at rated power was reported 96%. Moreover, in the proposed structure, the voltage stress of capacitors, diodes and switches reaches the maximum value of 63%, 83% and 41% of the output voltage, respectively; which are promising values. Finally, to verify the performance of the proposed converter and the relationships obtained, a 1kW prototype is built in the laboratory to demonstrate the efficiency of the proposed converter.
 

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The global transition towards renewable energy necessitates efficient energy storage solutions to address the intermittency of renewable sources. Lithium-ion batteries (LIBs), widely utilized in electric vehicles (EVs) for their high energy density and efficiency, yet their performance at low temperatures remains a challenge. This study investigates the influence of electrolyte solvent composition on LIB performance under low-temperature conditions. Three electrolytes were studied: a standard electrolyte (STDE) comprising 1 M LiPF₆ in ethylene carbonate (EC) and diethyl carbonate (DEC), a low-temperature electrolyte (LTE) consisting of 1 M LiPF₆ in EC, ethyl methyl carbonate (EMC), and ethyl acetate (EA), and a long-cycle-life electrolyte (LCLE) containing 1 M LiPF₆ in EC/EMC. The EIS results revealed significant differences in resistance values among the electrolytes at varying temperatures. Specifically, at 0 °C, the STDE exhibited a charge transfer resistance (R_ct) of 1055.3 Ω and a solid electrolyte interface resistance (R_SEI) of 803.4 Ω, whereas the LTE showed a substantially lower R_ct of 507.4 Ω and R_SEI of 64.2 Ω, indicating superior low-temperature performance. Similarly, at -20 °C, the R_ct values for STDE, LTE, and LCLE were 8878.6 Ω, 854.2 Ω, and 15622 Ω, respectively, with corresponding R_SEI values of 172.1 Ω, 92.4 Ω, and 2364 Ω. Notably, the addition of EA in the LTE formulation contributed to enhanced low-temperature performance, likely by lowering the overall viscosity of the electrolyte mixture and improving ionic mobility. This study demonstrates the critical role of solvent composition, particularly EA, in optimizing LIB performance for cold climate applications.
 

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High-entropy oxides (HEOs) are single-phase crystal structures composed of multiple metal elements that provide great potential for energy storage applications due to the synergistic effect of various metal species. They are considered effective anode materials for high-performance lithium-ion batteries (LIBs) because of their structural stability, high electronic conductivity, and ability to create anode materials with novel structures using several elemental compounds. Because the effects of different types of electrochemically active elements on the properties of anode materials are unknown, it is necessary to develop HEOs and investigate their properties. Herein, to explore the electrochemical properties of HEOs by changing the content of cations with various mechanisms for storing lithium, we prepared three samples of HEOs with spinel structure using the solid-state method, one of which is equimolar ((MgNiTiFeZn)_0.6O₄) and two numbers are near-equimolar ((Mg_0.6Ni_0.6Ti_0.3Fe_0.9Zn_0.6)O₄ and (Mg_0.6Ni_0.6Ti_0.3Zn_0.9Fe_0.6)O₄)). For structural properties determination, X-ray diffraction analysis was used. The results confirmed the formation of three single-phase high-entropy oxides.
Electrochemical tests indicated the structural stability of three compounds of high entropy oxides, and the composition of (MgNiTiFeZn)_0.6O₄, relative to the others, has better rate capability (163 mAhg⁻¹ at 1000 mAg^–1) and higher discharge capacity (220 mAhg⁻¹ at 200 mAg^–1) after 200 cycles.

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A novel liquid cooling system for pouch-type lithium-ion batteries (LIBs) is proposed by focousing on uniform temperatue disturbution and effective heat dissipation. The system utilizes a michrochannel cold plate with an innovative coolant disturbution design. This study proposes a novel microchannel disturbution path design with each microchannel dimensioning 1 mm² and embeded in the battery's ciritical region to enhance the thermal contact among the LIB and the microchannels. This study aims to simulate and evaluate the performance of cooling system under varius Iranian environmental conditions (Tehran, Shiraz, Isfahan, and Bandar Abbas) and operational parametrs (channel pattern, flow rate) to achieve optimal battery temperature and reduce energy consumption.