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In recent years, improvements in the fuel economy and exhaust emission performance of internal combustion engines have been increasingly required by regulatory agencies. One of the salient concerns regarding general purpose engines is the larger amount of CO emissions with which they are associated, compared with CO emissions from automobile engines. To reduce CO and other exhaust emissions while maintaining high fuel efficiency, the optimization of total engine system, including various design parameters, is essential. In the engine system optimization process, cycle simulation using 0-D and 1-D engine models are highly useful. To define an optimum design, the model used for the cycle simulation must be capable of predicting the effects of various parameters on the engine performance. In this study, a model for predicting the performance of a general purpose SI (Spark Ignited) engine is developed based on the commercially available engine simulation software, GT-POWER.

In CFD (Computational Fluid Dynamics) verification of vehicle aerodynamics, detailed velocity measurements are required. The conventional 2D-PIV (Two Dimensional Particle Image Velocimetry) needs at least twice the number of operations to measure the three components of velocity ( u,v,w ), thus it is difficult to set up precise measurement positions. Furthermore, there are some areas where measurements are rendered impossible due to the relative position of the object and the optical system. That is why the acquisition of detailed velocity data around a vehicle has not yet been attained. In this study, a detailed velocity measurement was conducted using a 3D-PIV measurement system. The measurement target was a quarter scale SAE standard vehicle model. The wind tunnel system which was also designed for a quarter scale car model was utilized. It consisted of a moving belt and a boundary suction system.

A numerical calculation method, which enables the analysis of gear train behavior including non-linear elements in a motorcycle engine, was established. During the modeling process, it was confirmed that factors such as bearing distortion, radial bearing clearance and elastic deformation of a tooth flank could not be neglected because they effect the rotation behavior. To keep a high accuracy, those factors were included in the simulation model, after they were converted into the rigidity elements along the rotational direction of each gear model. In addition, the model was combined with a crankshaft behavior calculation model for a driving and excitation source. A time domain numerical integration method was used to perform the transient response simulation across a wide range of engine speeds. A jump phenomenon of response behavior of the driven gear was predicted that is a characteristic of non-linear response. The phenomenon was also observed in a physical test.

Triggered explosions are increasingly becoming common in the world today leading to the loss of precious lives under the most unexpected circumstances. In most scenarios, ordinary citizens are the targets of such attacks, making it essential to design countermeasures in open areas as well as in mobility systems to minimize the destructive effects of such explosive-induced blasts. It would be rather difficult and to an extent risky to carry out physical experiments mimicking blasts in real world scenarios. In terms of mechanics, the problem is essentially one of fluid-structure interaction in which pressure waves in the surrounding air are generated by detonating an explosive charge which then have the potential to cause severe damage to any obstacle on the path of these high-energy waves.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

A computer simulation method for motorcycle rider motion in a collision on a passenger car has been developed. The computer simulation results were in two cases of collision, at 45 degree and 90 degree angles against the side of a passenger car. The simulated results were compared to the test results for validation. The simulation software of explicit finite element method (FEM) has been used, because of its capability for expressing accurate shape and deformation. The mesh size was determined with consideration for simulation accuracy and calculation time, and an FEM model of a motorcycle, an airbag, a dummy, a helmet and a passenger car were built. To shorten the calculation time, a part of the model was regarded as a rigid body and eliminated from the contact areas. As a result, highly accurate dummy posture and head velocity at the time of contact on the ground were simulated in the two cases of collision.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

Microprocessors and microcontrollers are now widely used in automobiles. Microprocessor systems contain sources of interrupt and interrupt service routines, which are software components executed in response to the assertion of an interrupt in hardware. A major problem in designing the software of microprocessor systems is the analytical treatment of interrupt latency. Because multiple interrupt service routines are executed on the same CPU, they compete for the CPU and interfere with each other's latency requirements. Here, interrupt latency is defined as the delay between the assertion of the interrupt in hardware and the start of execution of the associated interrupt service routine. It is estimated that 80% of intermittent bugs in small microprocessor software loads are due to improper treatment of interrupts. Until this work, there is no analytic method for analyzing a particular system to determine if it may violate interrupt latency requirements.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

The paper focuses on various important decisions of verification and testing plans of the product during its design and production stages. In most of the product and process development projects, decisions on verification and testing are ad-hoc or based on traditions. Such decisions never guarantee the performance of the product as planned, during its whole life cycle. We propose an analytical approach to provide the concrete base for such crucial decisions of verification planning. Accordingly, a mathematical model is presented. Also, a case study of an automotive Electro-mechanical product is included to illustrate the application of the model.

Periprosthetic fractures refer to the fractures that occur in the vicinity of the implants of joint replacement arthroplasty. Most of the fractures during an automotive frontal collision involve the long bones of the lower limbs (femur and tibia). Since the prevalence of persons living with lower limb joint prostheses is increasing, periprosthetic fractures that occur during vehicular accidents are likely to become a considerable burden on health care systems. It is estimated that approximately 4.0 million adults in the U.S. currently live with Total Knee Replacement (TKR) implants. Therefore, it is essential to study the injury patterns that occur in the long bone of a lower limb containing a total knee prosthesis. The aim of the present study is to develop an advanced finite element model that simulates the possible fracture patterns that are likely during vehicular accidents involving occupants who have knee joint prostheses in situ.

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.

This research investigates the variation of pedestrian stance in pedestrian-automobile impact using a validated multi-body vehicle and human model. Detailed vehicle models of a small family car and a sport utility vehicle (SUV) are developed and validated for impact with a 50th percentile human male anthropometric ellipsoid model, and different pedestrian stances (struck limb forward, feet together, and struck limb backward) are investigated. The models calculate the physical trajectory of the multi-body models including head and torso accelerations, as well as pelvic force loads. This study shows that lower limb orientation during a pedestrian-automobile impact plays a dominant role in upper body kinematics of the pedestrian. Specifically, stance has a substantial effect on the subsequent impacts of the head and thorax with the vehicle. The variation in stance can change the severity of an injury incurred during an impact by changing the impact region.

In order to minimize occupant injury in a vehicle collision, an approach was attempted to address this issue by optimizing the waveform of the vehicle body deceleration to reduce the maximum deceleration applied to the occupant. A previous study has shown that the mathematical solution to the optimal vehicle deceleration waveform comprised three stages: high deceleration, negative deceleration, and constant deceleration. A kinematic model with separated mass of the vehicle was devised to generate the optimal vehicle deceleration waveform comprising three stages including a one with negative deceleration in the middle. The validity of this model has been confirmed by a mathematical study on a one-dimensional lumped mass model. The optimal vehicle deceleration waveform generated by this method was then validated by a three-dimensional dummy simulation.

In order to minimize occupant injury in a vehicle crash, an approach was attempted to address this issue by making the wave form of vehicle body deceleration optimal to lower the maximum value of the occupant deceleration. Prior study shows that the mathematical solutions for the optimal vehicle deceleration wave form feature consisting of three aspects: high deceleration, negative deceleration, and constant deceleration. A kinematical model which has separated mass of the vehicle was devised to generate an optimal vehicle deceleration wave form which consists of three segments including a segment of negative deceleration in the middle. The validity of this model has been certified by a mathematical study by using a one-dimensional lumped mass model. The effectiveness of the optimal vehicle deceleration wave form generated by this method was validated by a simulation with a three-dimensional dummy.

A new friction testing system has been designed and built to simulate the actual engine conditions in friction and wear test of piston-ring and cylinder liner assembly. Experimental data has been developed as Friction Coefficient / Crank Angle Degree diagrams including the effects of running speed (500 and 700 rpm) and ring normal load. Surface roughness profilocorder traces were obtained for tested samples. Mixed lubrication regime observed in the most part of the test range. New cylinder bore materials and lubricants can be screened easily and more reliable simulated engine friction data can be collected using this technique.