Showing 72 results for Vehicle
Mr. Hamid Rahmanei, Dr. Abbas Aliabadi, Prof. Ali Ghaffari, Prof. Shahram Azadi,
Volume 13, Issue 2 (6-2023)
Abstract
The coordinated control of autonomous electric vehicles with in-wheel motors is classified as over-actuated control problems requiring a precise control allocation strategy. This paper addresses the trajectory tracking problem of autonomous electric vehicles equipped with four independent in-wheel motors and active front steering. Unlike other available methods presenting optimization formulation to handle the redundancy, in this paper, the constraints have been applied directly using the kinematic relations of each wheel. Four separate sliding mode controllers are designed in such a way that they ensure the convergence of tracking errors, in addition to incorporating the parametric and modeling uncertainties. The lateral controller is also designed to determine the front steering angles to eliminate lateral tracking errors. To appraise the performance of the proposed control strategy, a co-simulation is carried out in MATLAB/Simulink and Carsim software. The results show that the proposed control strategy has enabled the vehicle to follow the reference path and has converged the errors of longitudinal and lateral positions, velocity, heading angle, and yaw rate. Furthermore, the proposed control system shows promising results in the presence of uncertainties including the mass and moment of inertia, friction coefficient, and the wind disturbances.
Mr Arash Darvish Damavandi, Dr Behrooz Mashhdi, Dr Masoud Masih-Tehrani,
Volume 13, Issue 3 (9-2023)
Abstract
This paper investigates the performance of the hydraulically interconnected suspension system with the full vehicle model of ride and handling. A sensitivity analysis has been performed by changing the coefficients of the cylinder and accumulator valves and the initial conditions of the accumulators in the default hydraulic circuits to determine the effect on the frequency and damping of the system response such as roll, pitch, and bounce. This study highlights the importance of the influence of all system parameters to investigate vehicle vibration characteristics. The results provide valuable insights for designers and engineers working on improving automotive suspension system performance. Damping and frequency of modes change up to 179% with the change of cylinder valves and 141% with the change of accumulator valves and 74% for the initial pressure of accumulators change in mentioned range.
Mustafa Mirtabaee, Mohammad Abasi,
Volume 13, Issue 4 (12-2023)
Abstract
Protection of Armor Vehicles and military truck Occupants Against Explosion Mine and IED is the most important Parameter for comprehensive performance evaluation of armored vehicle. Armored Vehicle components Specifically Hull Floor Must be Able to Disperse Blast Shock Waves and Resist Against the structural Fracture. Analysis of the War Documents proves that flat hulls with thin-walled steel cannot resist against Anti-Tank Mines. In Recent years, development of V-shape Hull configurations Consider as an efficient Approach to improve Safety of armored vehicles. In the new generation of Armor Vehicle, Monocoque chassis combined with V-shape hull, But Replacement of All of the Old Armor Vehicle in the Defense Industry is not cost effective. So, there is an urgent need to develop the efficient strategy for enhancing the protection level of old armor vehicle. Since most of the armored vehicles used in the armies of different countries were designed and built in the past years, it is very likely that the safety standards have not been fully observed in them. Therefore, it is of great importance to provide a simple and low-cost plan for the reliable upgrade of such armored and logistics vehicles. In this article, by investigating the effect of placing V-shaped composite panels in three case studies, we were able to reduce the acceleration of the center of mass of the passenger compartment by approximately 7 times, in addition to reducing displacement by 50% on average. In addition, the explosion products were not able to penetrate into the cabin.
Dr. Pezhman Bayat, Dr. Peyman Bayat, Dr. Abbas Fattahi Meyabadi,
Volume 14, Issue 1 (3-2024)
Abstract
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.
Seied Isa Koranian, Mahdi Gholampour, Hamid Mazandarani,
Volume 14, Issue 1 (3-2024)
Abstract
Harnessing nanomaterials and the piezo-phototronic effect, we engineered a high-performance ultraviolet (UV) photodetector (PD), unveiling a new frontier in optoelectronics. This novel device seamlessly integrates zinc oxide nanorods (ZnO NRs) onto a flexible polyethylene terephthalate- indium tin oxide (PET-ITO) substrate through a straightforward and efficient hydrothermal process. This unique nanostructure design outshines its competitors, producing significantly higher current under UV illumination despite a comparable detection area. The plot thickens with the intriguing "piezo-phototronic effect," where applying pressure under UV light amplifies the current and overall device efficiency. This groundbreaking discovery paves the way for cutting-edge optoelectronic applications, where nanomaterials and the piezo-phototronic effect join forces to redefine performance.
Mr Seyed Amir Mohammad Managheb, Mr Hamid Rahmanei, Dr Ali Ghaffari,
Volume 14, Issue 1 (3-2024)
Abstract
The turn-around task is one of the challenging maneuvers in automated driving which requires intricate decision making, planning and control, concomitantly. During automatic turn-around maneuver, the path curvature is too large which makes the constraints of the system severely restrain the path tracking performance. This paper highlights the path planning and control design for single and multi-point turn of autonomous vehicles. The preliminaries of the turn-around task including environment, vehicle modeling, and equipment are described. Then, a predictive approach is proposed for planning and control of the vehicle. In this approach, by taking the observation of the road and vehicle conditions into account and considering the actuator constraints in cost function, a decision is made regarding the minimum number of steering to execute turn-around. The constraints are imposed on the speed, steering angle, and their rates. Moreover, the collision avoidance with road boundaries is developed based on the GJK algorithm. According to the simulation results, the proposed system adopts the minimum number of appropriate steering commands while incorporating the constraints of the actuators and avoiding collisions. The findings demonstrate the good performance of the proposed approach in both path design and tracking for single- and multi-point turns.
Seied Isa Koranian, Mahdi Gholampour, Hamid Mazandarani,
Volume 14, Issue 2 (6-2024)
Abstract
Fueled by their potential for energy harvesting, ZnO nanorods (NRs) have sparked considerable enthusiasm in the development of piezoelectric nanogenerators in the last decade. This is attributed to their exceptional piezoelectric properties, semiconducting nature, cost-effectiveness, abundance, chemical stability in the presence of air, and, the availability of diverse and straightforward crystal growth technologies. This study explores and compares the piezoelectric properties of two promising nanostructured ZnO architectures: thin films deposited via radiofrequency (RF) magnetron sputtering and well-aligned nanorod arrays grown using a hydrothermal process. Both structures are fabricated on flexible polyethylene terephthalate (PET) with an indium tin oxide (ITO) electrode (PET-ITO substrate), presenting valuable options for flexible piezoelectric devices. By directly comparing these distinct morphologies, we provide insights into their respective advantages and limitations for energy harvesting and sensor applications. The investigation into the piezoelectric properties of ZnO NRs involved the construction of an actual piezoelectric nanogenerator. This device demonstrated a direct correlation between applied mechanical forces and the resultant voltage outputs. It was observed that when the same external force was applied to both devices, the ZnO NRs-based piezoelectric nanogenerator (PENG) exhibited a higher output voltage compared to the other device.
Seyed Reza Hosseini, Mahdi Moghimi, Norouz Mohammad Nouri,
Volume 14, Issue 3 (9-2024)
Abstract
The impact of a supercooled droplet on a surface is a primary challenge of many industrial and aeronautical processes. However, in some cases, such as frost formation on vehicle windshields or wind turbine blades, the supercooled droplet collision does not occur in stagnant air. In this study, for the first time, the effects of the air transverse flow (ATF) on the thermal-fluid behavior of a supercooled droplet were investigated numerically. Also, different patterns of a superhydrophobic pillared surface were used in 24 three-dimensional simulations in ANSYS Fluent software. The volume of fluid method is chosen for the simulation of the multiphase flow. The freezing model is improved by the supercooling temperature consideration method. The results show that the ATF velocity reduces the separation time exponentially and helps the droplet bounce from the surface before freezing inception. However, the excessive increase in ATF velocity has the opposite effect and may prevent the droplet from detaching the surface due to notable drag. The best value of the ATF velocity is obtained to be 8 m/s , which reduces the separation time exponentially from 16.3 ms to 12.5 ms for a cold surface with a simple pillar pattern. The separation time is entirely affected by the simulation conditions and varies from 11.85 ms to 29.2 ms . The maximum spreading factor, despite the separation time, is seriously influenced by the void fraction percentage of different pillared surfaces and varies from 1.53 to 1.69.
Mr. Mohammad Hossein Nahani, Dr. Gholam Reza Molaeimanesh, Dr. Masoud Dahmardeh,
Volume 14, Issue 4 (12-2024)
Abstract
The transition from traditional internal combustion engine vehicles to electric vehicles is in progress. With their high energy density, low self-discharge rates, long cycle life, and absence of memory effects, lithium-ion batteries have become the primary power source for alternative vehicles. Throughout the battery's lifespan, its performance or health gradually deteriorates due to irreversible physical and chemical changes. Depending on the specific aging mechanisms, a battery may lose capacity or face increased internal resistance. Growing awareness of the importance of environmental protection and the potential implications associated with products and services has spurred interest in developing methods to better understand and address these impacts. Life cycle assessment is a method used to examine the environmental effects associated with all stages of product production. This study compares the operational conditions of an electric vehicle equipped with both new and old battery packs. The performance difference indicates that the vehicle with the aged battery has 17% less capacity, operates over 20% weaker in range, and its ohmic resistance increases by up to 150%. From a well-to-wheel perspective, using an electric vehicle with an old battery could result in a 2% increase in carbon dioxide emissions, reaching 56.638 g CO₂ equivalent per kilometer.
Amir Ansari Laleh, Mohammad Hasan Shojaeefard,
Volume 14, Issue 4 (12-2024)
Abstract
Lithium-ion batteries hold great promise for addressing environmental and energy challenges, driving their increased adoption in electric vehicles. Their advantages include stability, high energy density, low self-discharge, and long lifespan. However, both high and low temperatures pose significant challenges. High temperatures can lead to thermal runaway and safety hazards such as short circuits and explosions, while low temperatures can promote the formation of lithium dendrites, resulting in degradation and performance issues. To mitigate these thermal challenges, phase change materials (PCMs) have emerged as a promising solution for battery thermal management systems (BTMS). This review provides a comprehensive overview of PCMs and their application in BTMS. We categorize PCMs used in BTMS based on their modified filler materials and functionalities, including carbon-based (carbon fiber-PCM composites, carbon nanotube-PCM composites, and expanded graphite-PCM composites), metal foam, metal mesh, and organic and inorganic materials. Both inorganic and carbon-based materials can serve as highly thermally conductive encapsulants and fillers for PCMs. Finally, we present a thorough review of recent research on the thermal properties of modified PCMs and their impact on BTMS performance, including a detailed discussion of PCM performance metrics and selection criteria.
Ehsan Vakili, Behrooz Mashadi, Abdollah Amirkhani,
Volume 15, Issue 1 (3-2025)
Abstract
Ensuring that ethically sound decisions are made under complex, real-world conditions is a central challenge in deploying autonomous vehicles (AVs). This paper introduces a human-centric risk mitigation framework using Deep Q-Networks (DQNs) and a specially designed reward function to minimize the likelihood of fatal injuries, passenger harm, and vehicle damage. The approach uses a comprehensive state representation that captures the AV’s dynamics and its surroundings (including the identification of vulnerable road users), and it explicitly prioritizes human safety in the decision-making process. The proposed DQN policy is evaluated in the CARLA simulator across three ethically challenging scenarios: a malfunctioning traffic signal, a cyclist’s sudden swerve, and a child running into the street. In these scenarios, the DQN-based policy consistently minimizes severe outcomes and prioritizes the protection of vulnerable road users, outperforming a conventional collision-avoidance strategy in terms of safety. These findings demonstrate the feasibility of deep reinforcement learning for ethically aligned decision-making in AVs and point toward a pathway for developing safer and more socially responsible autonomous transportation systems.
Dr. Alireza Sobbouhi, Mohammad Mozaffari,
Volume 15, Issue 2 (6-2025)
Abstract
The high penetration of renewable energy sources (RES) makes the power system unreliable due to its uncertain nature. In this paper, the quantifying impact of electric vehicles (EV) charging and discharging on power system reliability and relieving the congestion is analyzed. The proposed reliability assessment is formulated by considering generation and demand interruption costs for N-1 contingency criteria. The proposed algorithm manages the optimal scheduling of EV to mitigate the uncertainties associated with RES and relieving the congestion. The impact of EV charging and discharging on expected energy not supplied (EENS) and expected interruption cost (ECOST) for generating companies (GENCOs), transmission companies (TRANSCOs), customers, and entire power system are calculated. The charging station of EV is selected by the trade-o_ between investment cost of EV and percentage change in EENS and ECOST value for the entire power system, GENCOs, TRANSCOs, and customers. The effectiveness of the proposed approach is tested on the modified IEEE RTS 24 bus system. The impact of EV charging stations on system reliability has been evaluated by quantifying the EENS and the ECOST across all available EV capacities. The results clearly demonstrate the improvement of system reliability and minimize the objective function consisting of generator re-dispatch and load curtailment considering N-1 contingency in the face of uncertainties of wind and solar generation sources by considering EV. The results show that EV can improve the reliability by about 40%. The problem is modeled in GAMS environment and solved using CONOPT as a nonlinear programming (NLP) solver.
