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Simulation has become an integral part in the design and development of an automotive air-conditioning (AC) system. Simulation is widely used for both system level and component level analyses and are carried out with one-dimensional (1D) and Computational Fluid Dynamics (CFD) tools. This paper describes a 1D approach to model refrigerant loop and vehicle cabin to simulate the soak and cool down analysis. Soak and cool down is one of the important tests that is carried out to test the performance of a heating, ventilation and air-conditioning (HVAC) system of a vehicle. Ability to simulate this cool down cycle is thus very useful. 1D modeling is done for the two-phase flow through the refrigerant loop and air flow across the heat exchangers and cabin with the commercial software AMESim. The model is able to predict refrigerant pressure and temperature inside the loop at different points in the cycle.

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.

Improving fuel efficiency and emission characteristics are significant issues in engine research. Because the engine has complex systems and various operating parameters, the experimental research is limited by cost and time. One-dimensional (1D) simulation has attracted the attention of researchers because of its effectiveness and relatively high accuracy. In a 1D simulation, the applied model must be accurate for the reliability of the simulation results. Because in-cylinder turbulence mainly determines the combustion characteristics, and mean flow velocity affects the in-cylinder heat transfer and efficiency in a spark-ignited (SI) engine, a number of sophisticated models have been developed to predict in-cylinder turbulence and mean flow velocity. In particular, tumble is a significant factor of in-cylinder turbulence in SI engine.

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

The role of 1D simulation tool is growing as the engine system is becoming more complex with the adoption of a variety of new technologies. For the reliability of the 1D simulation results, it is necessary to improve the accuracy and applicability of the combustion model implemented in the 1D simulation tool. Since the combustion process in SI engine is mainly determined by the turbulence, many models have been concentrating on the prediction of the evolution of in-cylinder turbulence intensity. In this study, two turbulence models which can resemble the turbulence intensity close to that of 3D CFD tool were utilized. The first model is dedicated to predicting the evolution of turbulence intensity during intake and compression strokes so that the turbulence intensity at the spark timing can be estimated properly. The second model is responsible for predicting the turbulence intensity of burned and unburned zone during the combustion process.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

Speed and accuracy are the critical needs in software for the modeling and simulation of vehicle cooling systems. Currently, there are two approaches used in commercially available thermal analysis software packages: 1) detailed modeling using complex and sophisticated three-dimensional (3D) heat transfer and computational fluid dynamics, and 2) rough modeling using one-dimensional (1D) simplistic network solvers (flow and thermal) for quick prediction of flow and thermal fields. The first approach offers accuracy at the cost of speed, while the second approach provides the simulation speed, sacrificing accuracy and can possibly lead to oversimplification. Therefore, the analyst is often forced to make a choice between the two approaches, or find a way to link or couple the two methods. The linking between one-dimensional and three-dimensional models using separate software packages has been attempted and successfully accomplished for a number of years.

The Toyota Prius Prime is a new generation of Toyota Prius plug-in hybrid electric vehicle, the electric drive range of which is 25 miles. This version is improved from the previous version by the addition of a one-way clutch between the engine and the planetary gear-set, which enables the generator to add electric propulsive force. The vehicle was analyzed, developed and validated based on test data from Argonne National Laboratory’s Advanced Powertrain Research Facility, where chassis dynamometer set temperature can be controlled in a thermal chamber. First, we analyzed and developed components such as engine, battery, motors, wheels and chassis, including thermal aspects based on test data. By developing models considering thermal aspects, it is possible to simulate the vehicle driving not only in normal temperatures but also in hot, cold, or warmed-up conditions.

The importance of radiative heat transfer on the combustion and soot formation characteristics under nominal ECN Spray A conditions has been studied numerically. The liquid n-dodecane fuel is injected with 1500 bar fuel pressure into the constant volume chamber at different ambient conditions. Radiation from both gas-phase as well as soot particles has been included and assumed as gray. Three different solvers for the radiative transfer equation have been employed: the discrete ordinate method, the spherical-harmonics method and the optically thin assumption. The radiation models have been coupled with the transported probability density function method for turbulent reactive flows and soot, where unresolved turbulent fluctuations in temperature and composition are included and therefore capturing turbulence-chemistry-soot-radiation interactions. Results show that the gas-phase (mostly CO2 ad H2O species) has a higher contribution to the net radiation heat transfer compared to soot.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

At the current stage of engine technology, diesel engines typically require diesel particulate filter (DPF) systems to meet recent particulate emissions standards. To assure the performance and reliability of DPF systems, profound understanding of filtration and regeneration mechanisms is required. Among extensive efforts for developing advanced DPF systems, the development of effective thermal management strategies, which control the thermal runaway taking place in oxidation of an excess amount of soot deposit in DPF, is quite challenging. This difficulty stems mainly from lack of sufficient knowledge and understanding about DPF regeneration mechanisms, which need detailed information about oxidation of diesel particulate matter (PM). Therefore, this work carried out a series of oxidation experiments of diesel particulates collected from a DPF on a diesel engine, and evaluated the oxidation rates of the samples using a thermo-gravimetric analyzer (TGA).

With the increasing demand for Battery Electric Vehicles (BEVs) capable of extended mileage, optimizing their efficiency has become paramount for manufacturers. However, the challenge lies in balancing the need for climate control within the cabin and precise thermal regulation of the battery, which can significantly reduce a vehicle's driving range, often leading to energy consumption exceeding 50% under severe weather conditions. To address these critical concerns, this study embarks on a comprehensive exploration of the impact of weather conditions on energy consumption and range for the 2019 Nissan Leaf Plus. The primary objective of this research is to enhance the understanding of thermal management for BEVs by introducing a sophisticated thermal management system model, along with detailed thermal models for both the battery and the cabin.

It is well known that thermal management is a key factor in design and performance analysis of Lithium-ion (Li-ion) battery, which is widely adopted for hybrid and electric vehicles. In this paper, an air cooled battery thermal management system design has been proposed and analyzed for mild hybrid vehicle application. Computational Fluid Dynamics (CFD) analysis was performed using CD-adapco's STAR-CCM+ solver and Battery Simulation Module (BMS) application to predict the temperature distribution within a module comprised of twelve 40Ah Superior Lithium Polymer Battery (SLPB) cells connected in series. The cells are cooled by air through aluminum cooling plate sandwiched in-between every pair of cells. The cooling plate has extended the cooling surface area exposed to cooling air flow. Cell level electrical and thermal simulation results were validated against experimental measurements.

In this paper a design methodology for automotive heat exchangers has been applied which brings robustness into the design process and helps to optimize the design goals: as to maintain an optimal coolant temperature and to limit the vehicle underhood air temperature within a tolerable limit. The most influential design factors for the heat exchangers which affect the goals have been identified with that process. The paper summarizes the optimization steps necessary to meet the optimal functional goals for the vehicle as mentioned above. Taguchi's [1] Design for Six Sigma (DFSS) methods have been employed to conduct this analysis in a robust way.

This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation and heat rejection losses of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology in use versus the technology being disabled (disabled equals fresh air-considered as the standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state.

The CFR engine is the widely accepted platform to test standard Research Octane Number (RON) and Motored Octane Number (MON) for determining anti-knock characteristics of motor fuels. With increasing interest in engine downsizing, up-torquing, and alternative fuels for modern spark ignition (SI) engines, there is a need to better understand the conditions that fuels are subjected to in the CFR engine during octane rating. To take into account fuel properties, such as fuel heat of vaporization, laminar flame speed and auto-ignition chemistry; and understand their impacts on combustion knock, it is essential to estimate accurate cylinder conditions. In this study, the CFR F1/F2 engine was modeled using GT-Power with the Three Pressure Analysis (TPA) and the model was validated for different fuels and engine conditions.

Response Surface Methodology (RSM) techniques are applied to develop brake specific fuel consumption (BSFC) maps of a test vehicle over standard drive cycles under various ambient conditions. This technique allows for modeling and predicting fuel consumption of an engine as a function of engine operating conditions. Results will be shown from Federal Test Procedure engine starts of 20°C, and colder conditions of -7°C. Fueling rates under a broad range of engine temperatures are presented. Analysis comparing oil and engine coolant as an input factor of the model is conducted. Analysis comparing the model to experimental datasets, as well as some details into the modeling development, will be presented. Although the methodology was applied to data collected from a vehicle, the same technique could be applied to engines run on dynamometers.