Browse Topic: Computer simulation
With the global issue of fossil fuel scarcity and the greenhouse effect, interest in electric vehicles (EVs) has surged recently. At that stage, because of the constraints of the energy density and battery performance degradation in low-temperature conditions, the mileage of EVs has been criticized. To guarantee battery performance, a battery thermal management system (BTMS) is applied to ensure battery operates in a suitable temperature range. Currently, in the industry, a settled temperature interval is set as criteria of positive thermal management activation, which is robust but leads to energy waste. BTMS has a kilowatt-level power usage under high- and low-temperature environments. Optimizing the BTMS control strategy becomes a potential solution to reduce energy consumption and overcome mileage issues. An appropriate system simulation model provides an effective tool to evaluate different BTMS control strategies. In this study, a predictive BTMS control strategy, which adjusts
Thermal Modeling plays an important role in high-fidelity vehicle modeling. As virtual platform development processes and methods are being increasingly leveraged to enable more virtualized development of powertrain, propulsion, control, and thermal management systems, the need for a fast yet high fidelity model only grows more urgent. Traditional modeling tools such as GT-Suite and AVL Simulation Suite can provide detailed modeling capabilities for both Powertrain and Thermal, however, simulation performance decreases with improved fidelity which is especially true in a co-simulation environment. In this paper, Matlab Simulink is proposed to be added to a co-simulation platform in order to substitute traditional tools. A powertrain model can be built from a mathematic model in Simulink while a Thermal model can be built in Simscape, which is a Simulink-based thermal modeling tool. Simscape provides physics-based thermal modeling similar to GT-Suite and AVL while reducing the overall
As the electrification of chassis systems accelerates, the demand for fail-safety strategies is increasing. In the past, the steering system was mechanically connected, so the driver could respond directly to some extent. However, the Steer-by-Wire (SbW) system is composed of the column and rack bar as electrical signals, so the importance of response strategies for steering system failure is gradually increasing. When a steering system failure occurs, a differential braking control using the difference in braking force between the left and right wheels was studied. Recently, some studies have been conducted to model the wheel reaction force generated during a differential braking. Since actual tires and road surfaces are nonlinear and cause large model errors, model-based control methods have limited performance. Also, in previous studies assumed that the driver normally operates the steering wheel in a failure situation. However, if limited to a situation such as autonomous driving
The transition to fully sustainable fuels, like ethanol, for Formula 1 power units in 2026 introduces challenges related to engine performance and emissions. The lower energy content of these fuels can have a negative impact on power output, while the increased levels of formaldehyde produced during combustion pose an environmental concern. This study aims to evaluate engine performance while meeting the FIA’s 2026 regulations using numerical simulations and to develop a method for estimating formaldehyde emissions produced during combustion. An F1 power unit model was developed in GT-Suite, incorporating all relevant regulations for 2026. The model was validated against literature data for combustion characteristics, such as laminar and turbulent flame speeds, and friction losses. Additionally, compliance with operational limits, such as energy flow restrictions, was confirmed. Suitable elementary and global reaction mechanisms for formation and destruction of formaldehyde were
Phase change energy storage devices are extensively utilized in latent heat thermal energy storage and hold significant potential for application in the thermal management of automotive batteries. By harnessing the high-density energy storage capabilities of phase change materials to absorb heat released by the batteries, followed by timely release and utilization, there is a substantial improvement in energy efficiency. However, the thermal conductivity of medium and low temperature phase change materials is poor, leading to its inefficient utilization. This paper focuses on optimizing the structure of a phase change heat exchanger in a phase change energy storage device to improve its performance. A basic design of the phase change heat exchanger is used as an example, and fin structure is added to enhance its heat exchange capabilities. A predictive surrogate model is built using numerical simulation, with the dimension and number of fins as design variables, and heat flow density
The metal inert-gas (MIG) welding technique employed for aluminum alloy automotive bumpers involve a complex thermo-mechanical coupling process at elevated temperatures. Attaining a globally optimal set of model parameters continues to represent a pivotal objective in the pursuit of reliable constitutive models that can facilitate precise simulation of the welding process. In this study, a novel piecewise modified Johnson-Cook (MJ-C) constitutive model that incorporates the strain-temperature coupling has been proposed and developed. A quasi-static uniaxial tensile model of the specimen is constructed based on ABAQUS and its secondary development, with model parameters calibrated via the second-generation non-dominated sorting genetic algorithm (NSGA-II) method. A finite element simulation model for T-joint welding is subsequently established, upon which numerical simulation analyses of both the welding temperature field and post-welding deformation can be conducted. The results
The research object of this project is the anti-slip and lateral stability control technique for a distributed three-axis drive vehicle. What differs from the traditional four-motor power system layout is that the third axle has two motors, while the second axle only has one motor. Compared with the traditional design, this layout can reduce dependence on battery performance and maintain motor operation in a high-efficiency range by switching between different operating modes. For example, when driving at high speeds, only the motor on the second axle works, which can improve motor efficiency. When accelerating or climbing, all motors work to provide a large power output. In the research, the vehicle model was first established in Simulink, and then co-simulated with TruckSim. The drive anti-slip control first identified the optimal slip rate for the road, and then used the sliding mode control to determine the driving torque for each wheel, achieving good control effects under various
Airborne compression ignition engines operating with aviation fuels are a promising option for reducing fuel consumption and increasing the range of hybrid-electric aircraft. However, the consistent ignition of Jet fuels at high-altitude conditions can be challenging. A potential solution to this problem is to ignite the fuel sprays by means of a glow-plug-based ignition assistant (IA) device. The interaction between the IA and the spray, and the subsequent combustion event result in thermal cycles that can significantly affect the IA’s durability. Therefore, designing an efficient and durable IA requires detailed understanding of the influence that the IA temperature and insertion depth have on the complex physics of fuel-air mixture ignition and flame propagation. The objective of this study is to design a conjugate heat transfer (CHT) modeling framework that can numerically replicate F-24 Jet fuel spray ignition using a glow-plug-based IA device in a rapid compression machine (RCM
The need for clean mobility launched multiple research directions in the powertrain field. While initially the battery electric vehicle (BEV) seemed the universal solution, the succession of pandemic emergencies and the resulting energetic crisis have defined a new scenario based on the multi-energy approach. One of the most promising technologies is the use of hydrogen in a fuel cell to generate electricity. This type of electric vehicle guarantees a shorter refueling time and a longer driving range than the battery electric one, becoming an enabling solution for long-haul or high-energy applications. In this study a combined 3D-CFD and 0D system analysis of an automotive Proton Exchange Membrane Fuel Cell (PEMFC) and system was carried out to provide a multi-scale analysis. In the first part, starting from a conventional parallel channel flow field configuration, the use of an optimization tool coupled with 3D-CFD simulations allowed to identify the optimal configuration in terms of
Conjugate heat transfer (CHT) analysis of electric motor cooling was performed, simulating both the standard and paperless stator designs, using the CFD software Simerics-MP+ to assess the predictive accuracy of the numerical simulations. The condition investigated involved the motor operating at 14,000 RPM. This high rotor speed was modeled using a novel hybrid approach for mesh rotation to make the problem more tractable. Oil and air, the two immiscible fluids, were modeled using the explicit interface-capturing Volume of Fluid (VOF) method. The traditional CHT approach is computationally expensive for electric motor cooling applications due to the heat transfer time scale differences between the fluid and the solid. Temperature changes in solids occur over a much slower time scale owning to their higher thermal inertia compared to fluids. Therefore, we model the fluid and solid domains separately and use a mixed-time scale approach to exchange the heat transfer data between them
The slope and curvature of spiral ramps in underground parking garages change continuously, and often lacks of predefined map information. Traditional planning algorithms is difficult to ensure safety and real-time performance for autonomous vehicles entering and exiting underground parking garages. Therefore, this study proposed the Model Predictive Path Integral (MPPI) method, focusing on solving motion planning problems in underground parking garages without predefined map information. This sample-based method to allows simultaneous online autonomous vehicle planning and tracking while not relying on predefined map information,along with adjusting the driving path accordingly. Key path points in the spiral ramp environment were defined by curvature, where reducing the dimensionality of the sampling space and optimizing the computational efficiency of sampled trajectories within the MPPI framework. This ensured the safety and computational speed of the improved MPPI method in motion
The Environmental Protection Agency’s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) modeling tool was initially created to simulate the Greenhouse Gas emissions from light-duty vehicles. ALPHA is used to predict tailpipe CO2 emissions and energy consumption from advanced automotive technologies. ALPHA is a physics-based, forward-looking vehicle computer simulation tool capable of analyzing various vehicle types with different powertrain technologies while replicating realistic vehicle behavior. ALPHA version 3.0 is the current version of the MATLAB/Simulink based software. Key changes made for ALPHA v3.0 include the addition of new light- and medium-duty vehicle models to support simulation of electrified vehicle architectures (hybrid, plug-in hybrid, and battery electric vehicles) aligning with the automotive industry transition towards electrified fleets. Each electrified vehicle model was tuned to replicate operational behavior of components (such as engine
The engineering design process employs an iterative approach in which proposed solutions are conceived, evaluated and refined until they satisfy a priori requirements - specifications. This iterative cycle generally uses computer aided designs (CAD), engineering analysis (CAE), numerical simulations per operating scenarios, and laboratory or field prototype testing. The availability of product data can be applied to assess the vehicle requirements – specifications to facilitate the next generation design. However, the calibration and use of a digital twin facilitates exploration of tradeoffs between engineering design, product manufacturing, and business demands, plus a desire to shorten the overall time. For instance, digital twin technology enables the swift evaluation of vehicle performance in various configurations and operating conditions. The question arises of how to best integrate digital twin technology into the design process. This paper will review the engineering design
The unicycle self-balancing mobility system offers superior maneuverability and flexibility due to its unique single-wheel grounding feature, which allows it to autonomously perform exploration and delivery tasks in narrow and rough terrains. In this paper, a unicycle self-balancing robot traveling on the lunar terrain is proposed for autonomous exploration on the lunar surface. First, a multi-body dynamics model of the robot is derived based on quasi-Hamilton equations. A three-dimensional terramechancis model is used to describe the interaction between the robot wheels and the lunar soil. To achieve stable control of the robot's attitude, series PID controllers are used for pitch and roll attitude self-balancing control as well as velocity control. The whole robot model and control strategy were built in MATLAB and the robot's traveling stability was analyzed on the lunar terrain.
The Distributed Drive Electric Vehicles (DDEVs) offer advantages such as independently controllable driving and braking forces at each wheel, rapid response, and precise control. These features enable effective electronic stability control (ESC) by appropriately distributing torque across each wheel. However, traditional ESC systems typically employ single-wheel hydraulic differential braking, failing to fully utilize the independent torque control capabilities of DDEVs. This study proposes a hierarchical control strategy for distributed driving and braking ESC based on particle filter (PF) and fuzzy integral sliding mode control (FISMC). First, the vehicle state estimation layer uses a three-degree-of-freedom vehicle model and the PF to estimate sideslip angle and vehicle speed. Next, the target torque decision layer includes a target speed tracking controller and a yaw moment decision controller. The yaw moment decision controller uses the FISMC to determine additional yaw moment by
Monocoque is a kind of integrated shell structure technology, which has gradually become the primary choice for various racing teams to make car bodies because of its advantages of small specific gravity and high specific strength. The unit of the monocoque is a carbon fiber composite sandwich structure, which is composed of two layers of carbon fiber skin inside and outside and core material between them. The inner and outer layers of the carbon fiber skin are stacked with carbon fiber composite materials of different directions and types.In this project, we plan to optimize the shape of the monocoque shell using the surface design software Alias, select core materials of different materials and structures, more advanced layups, and obtain feasible layup sequences and core material types through Ansys simulation and Matlab collaborative optimization, which will be verified by three-point bending experiments. Different from the previous lightweight work based a lot on experience, this
In the Baja race, off-road vehicles need to run under a variety of real and complex off-road conditions such as pebble road, shell pit, stone bad road, hump, water puddle, etc. In the process of this high-intensity and high-concentration race, the unoptimized design of the cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated. Cause the occurrence of security accidents. Moreover, lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable control matching, and these have a lot to do with unreasonable ergonomic design. In order to solve these problems, firstly establish the human body model of the driver, and then build the BSC racing car model by using 3D modeling software Catia. Then use the ergonomics simulation software Jack to analyze the visibility, accessibility and comfort. Based on the simulation
With the advancement of intelligent transportation and smart logistics systems, tractor semi-trailers have gradually become one of the primary modes of transport due to their substantial cargo capacity. However, the growing number of tractor semi-trailers has raised significant traffic safety concerns. Due to their significant spring mass and strong body strength, accidents involving tractor semitrailers often result in severe consequences. Active collision avoidance control strategies provide assurance for vehicle safety. However, existing research predominantly focuses on passenger cars and small commercial vehicles. Research specifically addressing tractor semi-trailers, which have longer bodies and more complex dynamic characteristics, is relatively sparse. Therefore, this paper proposes a collision risk assessment-based longitudinal collision avoidance control strategy for tractor semi-trailers with slip ratio control. Firstly, the paper introduces the braking characteristics and
Intelligent transportation systems and connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespread. Consequently, traditional human-driven vehicles (HDVs), CAVs, and human-driven connected and automated vehicles (HD-CAVs) will coexist on roads for the foreseeable future. Simultaneously, car-following behaviors in equilibrium and discretionary lane-changing behaviors make up the most common highway operations, which seriously affect traffic stability, efficiency and safety. Therefore, it’s necessary to analyze the impact of CAV technologies on both longitudinal and lateral performance of heterogeneous traffic flow. This paper extends longitudinal car-following models based on the intelligent driver model and lateral lane-changing models using the quintic polynomial curve to account for different vehicle types, considering human factors and cooperative adaptive cruise control. Then, this paper incorporates CAV penetration rates, shared autonomy rates
With the widespread application of the Automatic Emergency Braking System (AEB) in vehicles, its impact on pedestrian safety has received increasing attention. However, after the intervention of AEB, the kinematic characteristics of pedestrian leg collisions and their corresponding biological injury responses also change. At the same time, in order to accurately evaluate the pedestrian protection performance of vehicles, the current assessment regulations generally use advanced pedestrian protection leg impactors (aPLI) and rigid leg impactors (TRL) to simulate the movement and injury conditions of pedestrian legs. Based on this, in order to explore the collision boundary conditions and changes in injury between vehicles and APLI and TRL leg impactors under the action of AEB, this paper first analyzes the current passive and active assessment conditions. Secondly, the simulation software LS-DYNA is used to build a finite element model of APLI and TRL impactor-vehicle collisions to
Amphibious vehicles are widely used in civil and military scenarios due to their excellent driving performance in water and on land, unique application scenarios and rapid response capabilities. In the field of civil rescue, the hydrodynamic performance of amphibious vehicles directly affects the speed and accuracy of rescue, and is also related to the life safety of rescuers. In the existing research on the hydrodynamic performance of amphibious vehicles, seakeeping performance has always been the focus of research by researchers and amphibious vehicle manufacturers, but most of the existing research focuses on the navigation performance of amphibious vehicles in still water. In actual application scenarios, amphibious vehicles often face complex water conditions when performing emergency rescue tasks, so it is very important to study the navigation performance of amphibious vehicles in waves. Aiming at the goal of studying the navigation performance of amphibious vehicles in waves
In order to effectively improve the chassis handling stability and driving safety of intelligent electric vehicles (IEVs), especially in combing nonlinear observer and chassis control for improving road handling. Simultaneously, uncertainty with system input, are always existing, e.g., variable control boundary, varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis prescribed performance control strategy of IEVs become a hot topic in both academia and industry. To issue the above mentioned, a fuzzy sliding mode control method based on phase plane stability domain is proposed to enhance the vehicle’s chassis performance during complex driving scenarios. Firstly, a two-degree-of-freedom vehicle dynamics model, accounting for tire non-linearity, was established. Secondly, combing with phase plane theory, the stability domain boundary of vehicle yaw rate and side-slip phase plane based
Model-based developers are turning to DevOps principles and toolchains to increase engineering efficiency, improve model quality and to facilitate collaboration between large teams. Mature DevOps processes achieve these through automation. This paper demonstrates how integrating modern version control (Git) with collaborative development practices and automated quality enforcement can streamline workflows for large teams using Simulink. The focus is on enhancing model consistency, enabling team collaboration, and development speed.
This paper presents a comparative study between many control techniques to investigate the efficiency of the path tracking in various driving scenarios. In this study the Model predictive control (MPC), the adaptive model predictive control (AMPC) and the Stanley controller are employed to ensure that the vehicle follows reference paths accurately and robustly under varying environmental and vehicular conditions. Two driving scenarios are utilized S-road and Curved-road with MATLAB/Simulink under three different vehicle speeds to investigate vehicle performance employing the root mean square error (RMSE) as the performance evaluation function. Particle swarm optimization (PSO) utilized for optimizing the six parameters of the MPC prediction horizon (P), Control horizon(m), manipulated variable rates, manipulated variables weights and two output variables weights. Four objective functions are employed with PSO and compared to each other in terms of the time domain regarding the RMSE of
To take into account the drivers’ performance expectations in the comprehensive performance optimization of plug-in hybrid electric vehicles (PHEVs), we proposed an optimization method for the shift schedule of single-shaft parallel PHEVs considering drivers’ demands on both dynamic and economic performance. In accordance with torque distribution strategies developed for different working modes, the modes switching logic is formulated based on the demand torque along with the engine torque characteristics and the state of charge (SOC) of power battery. And a quantification model for driver’s intention is proposed using a fuzzy inference approach, which can compute the driver's dynamic and economic performance expectations using the driver's operation characteristics and vehicle status as input. With the help of a linear weighting method using the performance expectations as weights, a comprehensive performance evaluation function is constructed as the optimization objective of shift
New highly ductile advanced high strength steel (AHSS) grades with tensile strength greater than 980 MPa have been developed with the aim of achieving a combination of high strength and excellent formability. The new jetQTM-Family [1, 2] offers high local and global ductility, which is expected to contribute to the improvement of vehicle crash performance. For the reliable design and management of vehicle crash performance, material modeling, including work hardening behavior and material failure strain, plays an important role in numerical simulation. Especially, the accuracy of material failure prediction is important for the development of crash performance. In this study, the fracture behaviors of 980jetQTM, 1180jetQTM, and conventional Dual-Phase (DP) steels are investigated through simple tensile and V-bending fracture tests incorporating experimental-numerical hybrid ductile fracture analysis. Based on the experimental results, the ductile fracture parameters in the Hosford
This paper is a continuation of a previous effort to evaluate the post-impact motion of vehicles with high rotational velocity within various vehicle dynamic simulation softwares. To complete this goal, this paper utilizes a design of experiments (DOE) method. The previous papers analyzed four vehicle dynamic simulation software programs; HVE (SIMON and EDSMAC4), PC-Crash and VCRware, and applied the DOE to determine the most sensitive factors present in each simulation software. This paper will include Virtual Crash into this methodology to better understand the significant variables present within this simulation model. This paper will follow a similar DOE to that which was conducted in the previous paper. A total of 32 trials were conducted which analyzed ten factors. Aerodynamics, a factor included in the previous DOE, was not included within this DOE because it does not exist within Virtual Crash. The same three response variables from the previous DOE were measured to determine
The use of lithium-ion batteries in electric vehicles marks a major progression in the automotive sector. Energy storage systems extensively make use of these batteries. The extended life cycle, low self-discharge rates, high energy density, and eco-friendliness of lithium-ion batteries are well-known. However, Temperature sensitivity has an adverse effect on lithium-ion battery safety, durability, and performance. Thus, maintaining ideal operating conditions and reducing the chance of thermal runaway depend heavily on efficient thermal management. To address this, experimental study was conducted on various battery thermal management techniques, including active, passive, and hybrid approaches. These techniques were investigated for their cooling efficiencies under different operating conditions. The electro-thermal behavior of cylindrical lithium-ion battery cells, battery packs, and supervisory control techniques were simulated in the study using MATLAB Simulink, Simscape, and
Over the last two decades many improvements have been made in stock car racing driver safety. One of these is the head surround, which is rigidly secured to and an integral part of the NASCAR (National Association for Stock Car Auto Racing, LLC) seating environment and serves as an effective restraint for head protection during lateral and rear impacts. However, previous head impact material specifications were optimized for moderate to severe impacts and did not address low severity impacts that occur frequently during typical driving, such as race restart vehicle nose-to-tail contact. This study focused on developing a test methodology for comprehensive evaluation of rear head surround materials for low, moderate and severe impacts. Specifically, this study aimed to formulate a specification that maintains previous material performance during high speed impacts, while decreasing head accelerations at low speed impacts. Quasi-static and dynamic drop tower testing of sample materials
In-Mold Graining (IMG) is an innovative production technology applied to the skin wrapping of automotive interior components. In the design of automotive interior components of door panels and instrument clusters, to overcome process-related problems, such as the thinning of grain patterns and excessive reduction in thickness, simulation of the skin vacuum forming process is required. The Thermoplastic Olefin (TPO) skin material is investigated in this paper, and a viscoelastic mechanical model for this material is established. Dynamic Mechanical Analyzer (DMA) is utilized to perform scan for frequency and temperature, and the tested data is used to obtain key model parameters of the viscoelastic constitutive model. Based on the experimental data, the study explores how to calculate the relaxation time spectrum to describe the viscoelastic properties of TPO material during the vacuum forming process. Numerical simulation of the vacuum forming process of TPO material is conducted using
To address the challenges of complex operational simulation for Electric Vehicles (EVs) caused by spatial-temporal variations and driver behavior heterogeneity, this study introduces a dynamic operation simulation model that integrates both data-driven and physics-based principles, referred to as the Electric Vehicle-Dynamic Operation Simulation (EV-DOS) model. The physics-based component encompasses critical aspects such as the powertrain energy transfer module, heat transfer module, charge/discharge module, and battery state estimation module. The data-driven component derives key features and labels from second-by-second real-world vehicle driving status data and incorporates a Long Short-Term Memory (LSTM) network to develop a State-of-Health (SOH) prediction model for the EV power pack. This model framework combines the interpretability of physical modeling with the rapid simulation capabilities of data-driven techniques under dynamic operating conditions. Finally, this study
The drive unit, primarily consisting of an electric motor and a gearbox, needs to be cooled and lubricated for its long life and efficient performance. In an extreme drive cycle condition, the pickup tube to the pump may get exposed to air, leading to a substantial loss in line pressure and a drop in oil flow rate to the subsystems. An advanced Computational Fluid Dynamics (CFD) simulation can provide insights into the oil delivery system and help in improving the oil sump design, optimizing the position of the pickup tube to the pump and oil delivery lines. The current study employs a Volume of Fluid (VOF) based multiphase model implemented in a commercial CFD solver, Simerics-MP+. The drive unit lubrication system considered in the study consists of a gerotor pump, the entire oil delivery lines to the two subsystems and the drive unit casing. A multiphase simulation of the system with transient operation of the pump is computationally expensive. Therefore, a new methodology is
Platooning occurs when vehicles travel closely together to benefit from multi-vehicle movement, increased road capacity, and reduced fuel consumption. This study focused on reducing energy consumption under different driving scenarios and road conditions. To quantify the energy consumption, we first consider dynamic events that can affect driving, such as braking and sudden acceleration. In our experiments, we focused on modeling and analyzing the power consumption of autonomous platoons in a simulated environment, the main goal of which was to develop a clear understanding of the different driving and road factors influencing power consumption and to highlight key parameters. The key elements that influence the energy consumption can be identified by simulating multiple driving scenarios under different road conditions. The initial findings from the simulations suggest that by efficiently utilizing the inter-vehicle distances and keeping the vehicle movements concurrent, the power
This study investigates the impact of thermal imbalances on energy delivery and Battery State of Power (SoP) in immersion-cooled battery cells. It explores how these imbalances, which arise when cells within a module operate at different temperatures, lead to variations in internal resistance and inefficiencies in energy storage and discharge. Such imbalances critically affect the battery's SoP, representing the maximum charge or discharge power the system can support over specific time intervals. By analyzing SoP over 10-second durations and continuous, we assess how thermal imbalances influence both short-term and medium-term power capabilities. Temperature significantly impacts cell aging, and imbalances can accelerate degradation in some cells, ultimately affecting serviceability. To address these issues, we employ a high-level simulation framework that integrates advanced tools. GT-SUITE software optimizes thermal performance by adjusting coolant temperature and flow rate to
In a conventional cam-based valve actuation system, the valve events are tied up with the rotation of the crankshaft. In contrast, the electronic variable valve actuation (VVA) system enables flexible control of valve events independent of the crankshaft rotation. The present article discusses the development and control system design of a single-acting electro-pneumatic variable valve actuation (EPVVA) system that can be retrofitted to a conventional SI engine. The EPVVA system utilizes fast switching solenoid valves which modulate the flow of pressurized air in and out of a pneumatic chamber. The control system design is conducted in MATLAB Simulink platform using model-based approach. The valve actuator model is formulated such that it simulates the trajectory of the motion of the engine valve by numerically integrating a set of coupled differential equations that govern the thermo-fluid-dynamics and applied mechanics aspects of the valve actuation of the EPVVA system. The timings
Online road profiling capability is required for automotive active suspension systems to be realized in a consumer and commercial landscape. One challenge that impedes the realization of these systems is the need for the online road profiler to maintain an optimal spatial resolution of the oncoming road profile. Shifting of the road profiling sensor measurement frame of reference due to body motion experienced by the vehicle can negatively impact profiling accuracy. Prior work proposed a corrective look-ahead road profiling system (CLARPS) and demonstrated the CLARPS architecture and initial MATLAB/Simulink simulation environment. First, this work further develops the robust simulation environment. The simulation allows the look-ahead viewing angles to be optimized for the best road profile spatial resolution and facilitates a study on the impact of road profiler sensor location on the accuracy of the generated road profile. Second, this work introduces a lab-scale physical CLARPS
To address the issue of signal aliasing when multiple particles pass through a metallic particle sensor, which can lead to misidentification of particle count, we employ numerical simulation methods for an in-depth investigation. We developed a mathematical model of a three-coil inductive metal particle sensor to explore the signal variations induced by the passage of a single particle. We utilized micro-element simulation analysis to dissect the signal generated by a single particle, elucidating the underlying change process. Focusing on dual ferromagnetic particles as the subject of study, we conducted simulations and demodulation of the induced voltage under various combinations of sizes and spacings to investigate the influence patterns of dual adjacent ferromagnetic particles on the sensor's induced signal. Further research into the peak signals of different diameter particles at a constant spacing revealed that, for a given spacing, the ratio of peak signals between particles of
This paper presents the development of a new vehicle simulation software, the Power- and Usage-Based Simulator Tool (referred to as the Power-Based Model), designed to predict fuel consumption and evaluate advanced powertrain technologies for off-road mobile machinery. The Power-Based Model integrates current research on fuel consumption simulation in the off-road vehicle sector and serves as a platform for development of advanced powertrain technologies such as battery-electric and fuel cell powertrains. The tool predicts the battery capacity and hydrogen storage required for the transition to these advanced powertrains, allowing users to accurately calculate component sizes and reductions in fuel consumption. The Power-Based Model was developed with a strong focus on the unique operational characteristics of off-road machinery, ensuring that it realistically reflects real-world energy consumption and the competitive advantages of various fuel-saving technologies. This paper describes
The U.S. DRIVE Electrical and Electronics Technical Team has set a goal for 2025 to achieve a power density of 33 kW/L for electric vehicle (EV) motors [1]. The increase in motor power density is highly dependent on effective thermal management within the system, making active cooling techniques like oil-jet impingement essential for continued advancements. Due to the time and expense of physical experimentation, numerical simulations have become a preferred method for design testing and optimization. These simulations often simplify the motor-winding surface into a smooth cylinder, overlooking the actual corrugated surface due to windings, thus reducing computational resources and mesh complexity. However, the coil's corrugated surface affects flow turbulence and heat transfer rates. This study utilizes three-dimensional Computational Fluid Dynamics (CFD) simulations to investigate the impingement-cooling of an Automatic Transmission Fluid (ATF) jet on a corrugated surface that
Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on Nonlinear Model Predictive Control (NMPC) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual
A new hybrid power system was investigated by installing a motor on the axle of a conventional semi-trailer. The purpose is to reduce the fluctuation of longitudinal acceleration and improve driving comfort by filling the transmission output torque hole through the motor during the gear shift process. Models for the longitudinal motion of a commercial vehicle, the permanent magnet synchronous motor, and the motor power distribution method are established, and the system model is built using MATLAB/Simulink. The model-in-the-loop simulation control interface is created in ModelBase, and model-in-the-loop simulation under the full-throttle (WOT) and braking operating conditions is performed based on ModelBase. Due to the high-frequency jitter problem in the actual control of the motor, the torque output obtained from different control algorithms is investigated. Finally, the sliding mode control algorithm with perturbation observation is used to ensure the fast response and smoothness of
A multi-dimensional model of the spark ignition process for SI engines was developed as a user-defined function (UDF) integrated into the commercial engine simulation software CONVERGE CFD. The model presented in this paper simulates energy deposition from the ignition circuit into the fuel-air mixture inside the cylinder. The model is based on interaction and collision between electrons in the plasma arc and the gas molecules inside the cylinder using parameters from the ignition circuit and gas inside the cylinder. Full engine simulations using CONVERGE CFD with the developed ignition model including the ignition circuit model, arc propagation model, and energy deposition model were performed to evaluate the validity and performance of the model and to compare with the ignition model provided by CONVERGE CFD. A low turbulent port fuel injected single-cylinder CFR engine was used for comparison. Continuous multi-cycle RANS simulations showed cycle-to-cycle variations. The range of the
Virtual prototyping enables tires to be involved in automotive research and development (R&D) at an early stage, eliminating the trial-and-error process of physical tire samples and effectively reducing time and costs. Semi-empirical/empirical tire models are commonly used to evaluate vehicle-tire virtual mating. To parameterize these models, finite element (FE) simulations are necessary, involving combinations of sideslip, camber, and longitudinal slip under various loads. This paper identifies that when multiple inputs are combined, the FE simulation conditions become complex and numerous, presenting a significant challenge in virtual prototyping applications. Through an extensive analysis of more than ten tire prediction modeling methods and models in detail, this paper demonstrates the significant potential of tire prediction modeling in addressing this challenge. We begin with an overview of the current state of research in tire virtual prototyping, reviewing its application
Because the steer-by-wire (SBW) system cancels the mechanical connection between the steering wheel and the steering wheel in the traditional mechanical steering system (MSS), various road information on the road cannot be directly transmitted to the driver through the steering wheel in the form of road sense. Consequently, drivers are unable to genuinely perceive this road information, which adversely affects their control of the vehicle. This paper investigates the road perception simulation method for SBW systems. Initially, a dynamic model of the SBW system is developed, and its validity is confirmed under conditions of step changes in steering wheel angle and dual-shifting scenarios. A state estimation approach is employed to simulate road perception torque, and a corresponding torque calculation formula is derived based on the dynamic model of traditional steering systems. A two-degree-of-freedom vehicle model is constructed to independently compute the lateral force experienced
Sound pollution has become one of the major environmental concerns for the global automotive industry. Air Induction System (AIS) plays an important role in engine performance and vehicle noise. An ideal design of AIS provides debris-free air for combustion and reduces the engine noise that is heard while snorkeling. This work aims to correlate low-frequency engine order noise prediction at the compressor inlet and snorkel inlet for a 2.0L I4 turbo engine of a Plug-in hybrid vehicle (PHEV) for better acoustic performance without compromising on engine performance. 1D simulation software GT-POWER, Simcenter 3D, and Hypermesh are used for this work. Transmission loss (TL) results with respect to the frequency of the air-box with ducts and intake manifold with charge air cooler are plotted from 0 to 1000 Hz. The air intake system TL results show a good correlation between 3D and 1D till 600 Hz. Compressor and snorkel noise simulation results, especially the firing order and its harmonic
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