Automotive Science and Engineering

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This study examines how different porosity levels and perforation patterns affect the crushing performance of thin-walled cylindrical tubes under axial loading. Nonlinear explicit finite element simulations, validated by experiments, were performed on tubes with varying porosity ratios to assess deformation modes, peak crushing forces, and energy absorption efficiencies. The study's results indicate that perforated tubes have better energy absorption characteristics than non-perforated tubes, with a 7.83% improvement in the Specific Energy Absorption (SEA) value. The straight-type tube demonstrated a 1.75% higher Specific Energy Absorption (SEA) and 1.23% greater total energy absorption compared to the staggered arrangement. These findings suggest the effectiveness of the straight-type design for load-bearing and energy dissipation. This research offers insights into optimizing energy-absorbing structures for impact mitigation, suggesting that the straight-type configuration may be better when structural integrity and energy absorption are crucial.

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The escalating proliferation of electric vehicles (EVs) as a pivotal solution to address energy consumption and air pollution challenges within the transportation sector necessitates a comprehensive understanding of the factors influencing their performance and driving range. Among these factors, driving patterns exert a direct and significant impact on energy consumption and battery state. This study aims to quantify the influence of diverse driving cycles on the performance of an electric vehicle, specifically the Audi e-tron 50.   Utilizing Simcenter Amesim software, a longitudinal vehicle dynamics model, coupled with an equivalent circuit model (ECM) for the lithium-ion battery, was developed for simulation purposes. The vehicle's performance was evaluated under five distinct driving cycles, including global standards (WLTC, NEDC, HWFET) and two real-world driving cycles recorded in Tehran (Route1, Route2). Key parameters such as state of charge (SoC), depth of discharge (DoD), battery temperature, and estimated driving range were analyzed. The results revealed a significant impact of driving cycles on all investigated parameters. Driving cycles characterized by higher speeds and accelerations (e.g., WLTC and HWFET) led to increased specific energy consumption, accelerated temperature rise, and a notable reduction in estimated driving range (with the lowest range observed in WLTC). Conversely, milder urban driving cycles (particularly Route1) resulted in improved energy efficiency, minimal thermal stress, and the highest estimated driving range. These findings underscore the critical importance of considering real-world and localized driving patterns for accurate performance evaluation, range estimation, and the development of optimized energy management strategies in electric vehicles.
 

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Conventional diesel engine, hydraulic hybrid, and fully electric powertrain structures were modeled to assess fuel consumption in a sample urban refuse collection truck. The components utilized in the modeling include an internal combustion engine, transmission, electric motor, and battery. To this end, the vehicle's driving cycle is initially analyzed and characterized. The target vehicle is a light duty N series Isusu 8 tones truck. Based on the simulations conducted in the MATLAB/Simulink environment, the hydraulic hybrid configuration demonstrated the lowest fuel consumption for the Refuse truck vehicle, achieving 27.6 liters of diesel fuel per 100 kilometers. The fully electric configuration exhibited a fuel consumption value closely approaching that of the hydraulic hybrid. Eventually, based on the obtained results, the layout of the equipment for the finalized configurations was designed in the Autodesk Inventor software environment.

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Automotive radar systems operating in the 24 GHz band are widely used in Advanced Driver Assistance Systems (ADAS) due to their cost-effectiveness and robust performance across diverse environmental conditions. However, these systems face critical vulnerabilities from electromagnetic interference (EMI) and high-power microwave (HPM) threats, which can degrade detection accuracy. This study presents a novel plasma-based limiter employing a Gas Discharge Tube (GDT) within an optimized K-band waveguide (10.668 × 4.318 mm) filled with Rogers RO3035 dielectric (εr = 3.6). The design achieves exceptional metrics: 0.9 dB insertion loss and 21.5 dB return loss during normal operation, while providing over 30 dB isolation against HPM signals with a sub-100 ns response time. These characteristics position this solution as an industry-leading protection mechanism for next-generation automotive radars. 

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This study proposes a hierarchical nested cascade control framework to enhance voltage regulation and current management in fuel cell hybrid electric vehicles (FCHEVs). The architecture addresses limitations of conventional cascade control by reducing design complexity and improving resilience under dynamic and uncertain conditions. It integrates three coordinated layers: an outer control level (OCL) employing an adaptive proportional–integral controller for DC bus voltage regulation, and two internal layers, middle (MCL) and inner (ICL), implemented via backstepping controllers for precise current control of fuel cells, batteries, and supercapacitors. By combining nonlinear control with model reference adaptive control, the system dynamically tunes parameters to maintain voltage stability across variable load profiles. Simulations using the WLTC-Class 3 cycle show that the proposed strategy (Case 1) achieves superior battery sustainability, with a final SOC of 74.2%, compared to 71% and 72.5% in benchmark strategies (Cases 2 and 3). Under battery aging (20% increased resistance, 15% reduced capacity), DC bus voltage remains within ±3.5 V of the 380 V reference, with only 18% ripple increase and 0.8% additional SOC depletion. A resilience index of 96.5% confirms robustness, outperforming benchmarks (84.2%, 89.7%). To further validate performance under real-world urban conditions, date-specific driving cycles tailored for Shiraz city were employed. Results confirm the framework’s effectiveness in sustaining stability, efficiency, and scalability for next-generation FCHEV energy systems.