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Nowadays, what captures consumers' primary attention is how to purchase electric vehicles with long range and desirable price. Lightweight construction stands as one of the most effective approaches for prolonging range and lowering costs. As a consequence, it is particularly imperative to undertake lightweight design optimization for the battery bracket of new energy vehicles by applying 3D printing technology. To actualize this goal, Rhino software was initially employed for 3D modeling to design the battery bracket system for a pure electric vehicle in China. Subsequently, topology optimization design of the battery bracket was carried out by adopting Altair Inspire software. Last but not least, manufacturing and assembly inspection were completed using a 3D printer. The results show that the maximum displacement of the battery lower tray bracket after topology optimization is 3.20 mm, which is slightly higher than before, but still relatively small. The maximum Mises equivalent stress rose to 240.7 MPa post-optimization, but brought about a uniform stress distribution at the bottom of the bracket. In comparison, the minimum factor of safety met design requirements at 1. The mass was lessened to 0.348 kg, representing a 49.2% decrease in comparison with pre-optimization levels. The 3D-printed bracket was fabricated by employing a 3D printer, thereby achieving the aforementioned mass abatement. The battery pack parts exhibited a bright surface with low roughness and no discernible warping or deformation defects. As revealed by the assembly results, the components of the battery pack bracket are tightly coordinated with each other, with no evident assembly conflicts, revealing that the dimensional accuracy and fit of the completed parts meet production requirements. These findings lay solid groundwork for the mass production of high-performance battery pack brackets. [ABSTRACT FROM AUTHOR]

Interest towards electric vehicle adoption is on the rise due to the lower running and maintenance cost it offers, along with zero tailpipe emissions. Range anxiety is one of the only concern that affects the adoption of electric vehicles. The state of charge of the traction battery pack has to be accurately determined and provided to the user to avoid range anxiety. Minute battery parameters has to be considered to improve the accuracy of the state of charge determination. In order to overcome the problem of range anxiety, an innovative strategy that takes into account how vibrations affect the performance of EV batteries is developed in this research. By doing this, the state of charge estimation precision is improved and thereby raises the driver's faith in electric vehicles. The impacts and vibrations felt on the traction battery pack during driving would lead to heat generation. The heat generated is found to be highest when the vibrations resonate at the natural frequencies of the traction battery pack. The natural frequency of the battery pack is considered when the battery is kept in the battery chamber of the two-wheeler electric vehicle. The vibrations at natural frequency produces heat which is accounted for when the state of charge is determined. To obtain accurate state of charge estimation, a Kalman filter-based approach is used. The Kalman filter-based estimation uses the conventional methods which are the open circuit voltage method and the Coulomb counting method to improve the estimation process along with the consideration of the heat component due to vibrations and impact. The vibration analysis is performed using MATLAB, while the state of charge determination is implemented in hardware and the Kalman estimation done using Python. The system is modelled on an electric two-wheeler platform and the testing is done to compare the state of charge accuracy of the open circuit voltage method, the Coulomb counting method and the Kalman filter-based estimation approach. The inclusion of the vibrational heat analysis for State of Charge estimation in the hardware testing of the electric two-wheeler provides an accurate state of charge value. [ABSTRACT FROM AUTHOR]

Lithium‐ion cell chemistries are favored in the automotive sector, as they enable electric vehicles (EVs) to compete with traditional gasoline‐powered vehicles in terms of performance, range, and cost. The life and performance of these packs depend upon the Battery management system which monitors and controls the pack. The modeling, simulation, and analysis of a lithium‐ion battery pack that closely resembles an actual automobile battery are the focus of this paper. Real cells that are commercially available and specifically developed for automotive applications are modeled in the simulation environment. The cell characterization and formation of pack topology with heat exchange are addressed. A commercial electric car's power train model and EV dynamics are used in the simulation environment to test the modeled battery pack over various drive cycles. The performance analysis is upscaled by considering different aspects like resistive forces while driving, ambient temperature, initial conditions while the vehicle starts, etc. The battery manufacturer can verify the battery's performance under different load conditions, with a high degree of similarity to real‐world scenarios. The simulations are conducted on MATLAB/Simulink 2021b software. [ABSTRACT FROM AUTHOR]

Matching between low-voltage high-current capacity battery/fuel cell with high-voltage low-current motors in electric vehicles (EVs) requires paralleling-connection multi-stage power electronic converter with accurate modeling and control system. For high-voltage low-current drives of EVs with high-boosting/bucking gain, single-stage single-arm DC/DC converters suffer from unstable output voltage and the impractical choice of charging/discharging elements. Therefore, a multi-stage multi-arm DC/DC converter is researched to solve the problems of high boosting/bucking gain and minimized the voltage and current ripples. This paper presents parametric sizing, dynamic modeling, and analysis of all logical operational modes for a new high-gain DC/DC converter suitable for deployment in EV applications. The proposed topology composes of three-stage interleaved-input composed of cascaded two stages and double float-output as a third stage with bidirectional current capability. In this study, parametric design, and sizing for the three stages are performed according to the prerequisite ratings. Then, an analysis is conducted on rules of operating the DC/DC converter along with a discussion on considerations taken into account for such a critical design. An investigation of the dynamic behavior of the suggested DC/DC converter is carried out through a state-space model with switches’ states. Furthermore, a simulation and measurement-based validation of the derived mathematical models are conducted. The theoretical based analysis, design, and boosting gains are confirmed through a constructed and tested prototype given data on power supply and load utilization. A discussion on the choice of semiconductor equipment and reactive elements is provided for the proposed DC/DC converter. The experimental results show that the three stages can be used in a separate mode or in a cascaded booster.

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO 2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO 2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO 2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO 2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy. • A battery pack use-phase carbon footprint assessment strategy is proposed. • The carbon emissions for four battery pack subsystems are calculated. • Temperature has the greatest impact on the battery pack carbon emissions. [ABSTRACT FROM AUTHOR]

• The heat generation model for cylindrical Li-ion battery was built. • A liquid immersion cooling battery pack containing 60 batteries were established. • At 2C discharge rate, 0.5 L/min flow rate was recommended. • The battery pack can address localized high-rate discharge events (4.5C or 6.5C). • Liquid immersion cooling BTMSs have great heat dissipation performance. With the increasingly severe challenges of the thermal management of battery packs for electric vehicles, the liquid immersion cooling technology has gradually attracted more attention due to its superior characteristics such as high heat dissipation efficiency, well temperature uniformity and low risk of thermal runaway. To investigate the heat transfer characteristics of the liquid immersion cooling BTMSs, the 3D model of the 60-cell immersion cooling battery pack was established, and a well-established heat generation model that leveraged parameters derived from theoretical analysis and experiments was incorporated into the 3D simulation to analyze the thermal characteristics of battery pack. The simulation results showed that under the discharging rate of 2C, even with the lowest coolant flow rate in this work (0.2 L/min), no localized abnormal overheating within the battery pack was observed, and the highest temperature was 34.22 °C. The temperature uniformity within the battery pack improved with the increase of the coolant flow rate. It was recommended to maintain a flow rate above 0.5 L/min to ensure a temperature difference below 5 °C. The experimental apparatus of the immersion cooling battery pack was also developed to explore the heat dissipation and temperature uniformity at 2C discharge rate. The simulation results were in well agreement with the experimental results, with the deviation less than 0.43 °C when the flow rate exceeded 0.6 L/min. The effect of the localized high-rate discharge events (4.5C and 6.5C) at different battery pack locations on temperature distribution and uniformity was further discussed based on the verified 3D model. The results suggested that liquid immersion cooling systems offered promising potential for achieving both efficient heat dissipation and preventing thermal runaway in battery packs. [ABSTRACT FROM AUTHOR]

This comprehensive study delves deeply into the realm of electric vehicle (EV) battery temperature management, with a central focus on optimizing cooling systems using ethylene glycol solutions. The research rigorously examines the interplay between ethylene glycol concentrations and cooling methods on EV battery performance. ANSYS and MATLAB along with analytical methods were used for this project. Key findings reveal a consistent inverse relationship between ethylene glycol concentration and cooling efficiency, favoring lower concentrations. Indirect cooling, achieved with a 30% ethylene glycol solution, emerges as the most effective method, while direct cooling proves less efficient. Notably, mineral oil cooling at 0.04 m/s outperforms air cooling, albeit with higher energy consumption. Consequently, air cooling is recommended for smaller battery packs due to its lower power demand. The study also underscores the importance of selecting ethylene glycol concentrations based on environmental conditions, advocating lower concentrations for warmer climates and higher concentrations for colder regions. In summary, this research significantly advances EV technology by advocating for customized cooling system designs that consider environmental factors, battery specifications, and practical implementation. It provides a critical roadmap for enhancing EV thermal management systems' efficiency and sustainability. Further research is needed to explore the long-term effects of diverse cooling methodologies on battery longevity and performance within the practical constraints of EV integration. • Cooling effectiveness increases with lower concentration. • Indirect cooling outperforms direct methods. • Higher coolant flowrate enhances heat extraction but requires more energy. • A 50% ethylene glycol solution is suitable for most weather conditions. [ABSTRACT FROM AUTHOR]