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Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Internal combustion engine gets heated up due to continuous combustion of fuel. To keep engine working efficiently and prevent components damage due to very high temperature, the engine needs to be cooled down. Based on power output requirement and provision for cooling system, every engine has it’s unique cooling system. Liquid based cooling systems are majorly implemented in automobile. It’s important to keep in mind that during design phase that, cooling the engine will lower the power to fuel consumption ratio. Therefore, during lower ambient conditions, the cooling system should be able to uniformly increase the temperature of the engine components, engine oil and transmission oil. This is achieved by circulating the coolant through cooling jacket, engine oil heater and transmission oil heater, which will be heated by the combustion heat.

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.

Maintaining the fuel temperature and fuel system components below certain values is an important design objective. Predicting these temperatures is therefore one of the key parts of the vehicle’s thermal management process. One of the physical processes affecting fuel tank temperature is fuel vaporization, which is controlled by the vapor pressure in the tank, fuel composition and fuel temperature. Models are developed to enable the computation of the fuel temperature, fuel vaporization rate in the tank, fuel temperatures along the fuel supply lines, and follow its path to the charcoal canister and into the engine intake. For diesel fuel systems where a fuel return line is used to return excess fluid back to the fuel tank, an energy balance will be considered to calculate the heat added from the high-pressure pump and vehicle under-hood and underbody.

The performance and durability of the lead acid battery is highly dependent on the internal battery temperature. The changes in internal battery temperatures are caused by several factors including internal heat generation and external heat transfer from the vehicle under-hood environment. Internal heat generation depends on the battery charging strategy and electric loading. External heat transfer effects are caused by customer duty cycle, vehicle under-hood components and under-hood ambient air. During soak conditions, the ambient temperature can have significant effect on battery temperature after a long drive for example. Therefore, the temperature rise in a lead-acid battery must be controlled to improve its performance and durability. In this paper a thermal model for lead-acid battery is developed which integrates both internal and external factors along with customer duty cycle to predict battery temperature at various driving conditions.

In this paper we present an integrated approach which combines analysis of the effect of simultaneous variations in model input parameters on component or system temperatures. The sensitivity analysis can be conducted by varying model input parameters using specific values that may be of interest to the user. The alternative approach is to use a structured set of parameters generated in the form of a DFSS DOE matrix. The matrix represents a combination of simulation conditions which combine the control factors (CF) and noise factors. CF’s are the design parameters that the engineer can modify to achieve a robust design. Noise factors include parameters that are outside the control of the design engineer. In automotive thermal management, noise factors include changes in ambient temperature, exhaust gas temperatures or aging of exhaust system or heat shields for example.

Determining coolant flow distribution in a topologically complex flow path for efficient heat rejection from the critical regions of the engine is a challenge. However, with the established computational methodology, thermal response of an engine (via conjugate heat transfer) can be accurately predicted [1, 2] and improved upon via Design of Experiment (DOE) study in a relatively short timeframe. This paper describes a method to effectively distribute the coolant flow in the engine coolant cavities and evenly remove the heat from various components using a novel technique of optimization based on an approximation model. The current methodology involves the usage of a sampling technique to screen the design space and generate the simulation matrix. Isight, a process automation and design exploration software, is used to set the framework of this study with the engine thermal simulation setup done in the CFD solver, STAR-CCM+.

Engine mount is one of the temperature sensitive components in the vehicle under-hood. Due to increasing requirements for improved fuel economy, the under-hood thermal management has become very challenging in recent years. In order to study the effects of material thermal degradation on engine mount performance and durability; it is required to estimate the temperature of engine mount rubber during various driving conditions. The effect of temperature on physical properties of natural rubber can then be evaluated and the life of engine mount can be estimated. In this paper, a bench test is conducted where the engine mount is exposed to a step change in the environment around it, and the temperature of the rubber section is recorded at several points till a steady state temperature is reached. A time response curve is generated, from which a time constant is determined.

Piston temperature plays a major role in determining details of fuel spray vaporization, fuel film deposition and the resulting combustion in direct-injection engines. Due to different heat transfer properties that occur in optical and all-metal engines, it becomes an inevitable requirement to verify the piston temperatures in both engine configurations before carrying out optical engine studies. A novel Spot Infrared-based Temperature (SIR-T) technique was developed to measure the piston window temperature in an optical engine. Chromium spots of 200 nm thickness were vacuum-arc deposited at different locations on a sapphire window. An infrared (IR) camera was used to record the intensity of radiation emitted by the deposited spots. From a set of calibration experiments, a relation was established between the IR camera measurements of these spots and the surface temperature measured by a thermocouple.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

The trend to simultaneously improve fuel economy and engine performance has led to industry growth of turbocharged engines and as a result, the need to address their undesirable airborne noise attributes. This presents some unique engineering challenges as higher customer expectations for Noise Vibration Harshness (NVH), and other vehicle-level attributes increase over time. Turbocharged engines possess higher frequency noise content compared to naturally aspirated engines. Therefore, as an outcome, whoosh noise in the Air Induction System (AIS) during tip in conditions is an undesirable attribute that requires high frequency attenuation enablers. The traditional method for attenuation of this type of noise has been to use resonators which adds cost, weight and requires packaging space that is often at a premium in the under-hood environment.

One of the key inputs 1-D transient simulation takes is a detailed front end cooling flow map. These maps that are generated using a full vehicle Three-dimensional Computational Fluid Dynamics (3D CFD) model require expensive computational resources and time. This paper describes how an adaptive sampling of the design space allowed the reduction of computational efforts while keeping desired accuracy of the analysis. The idea of the method was to find a pattern of Design of Experiments (DOE) sampling points for 3D CFD simulations that would allow a creation of an approximation model accurate enough to predict output parameter values in the entire design space of interest. Three procedures were implemented to get the optimal sampling pattern.

A heat pipe is a self-operating device which is capable of transferring large amounts of heat with a minimum temperature differences between the hot end (evaporator) and the cold end (condenser). However, a limited number of research work or analysis [1,2,3,4,5,6,7,8,9] has been reported in automotive industry on the applications of heat pipes in power train cooling. The advantage of a heat pipe heat exchanger is the possibility to use a more compact and lighter radiator. In addition, the proposed radiator is expected to be more robust as it is less sensitive to variations in ambient temperatures. In this paper, a proposed design for an automotive heat exchanger is investigated. The proposed design is evaluated through thermal simulation of heat pipes using various design parameters. The analysis addresses the ability of the heat exchanger to maintain engine coolant temperature at acceptable limits under different loading conditions.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

This study focuses on how to predict hot spots of one of the cylinders of a V8 5.4 L FORD engine running at full load. The KIVA code with conjugate heat transfer capability to simulate the fast transient heat transfer process between the gas and the solid phases has been developed at the Michigan Technological University and will be used in this study. Liquid coolant flow was simulated using FLUENT and will be used as a boundary condition to account for the heat loss to the cooling fluid. In the first step of calculation, the coupling between the gas and the solid phases will be solved using the KIVA code. A 3D transient wall heat flux at the gas-solid interface is then compiled and used along with the heat loss information from the FLUENT data to obtain the temperature distribution for the engine metal components, such as cylinder wall, cylinder head, etc.

One-dimensional single-zone and two-zone analyses have been exercised to calculate the mass fraction burned in an engine operating on ethanol/gasoline-blended fuels using the cylinder pressure and volume data. The analyses include heat transfer and crevice volume effects on the calculated mass fraction burned. A comparison between the two methods is performed starting from the derivation of conservation of energy and the method to solve the mass fraction burned rates through the results including detailed explanation of the observed differences and trends. The apparent heat release method is used as a point of reference in the comparison process. Both models are solved using the LU matrix factorization and first-order Euler integration.

As the incentive to produce cleaner and more efficient engines increases, diesel engines will become a primary, worldwide solution. Producing diesel engines with higher efficiency and lower emissions requires a fundamental understanding of the interaction of the injected fuel with air as well as with the surfaces inside the combustion chamber. One aspect of this interaction is spray impingement on the piston surface. Impingement on the piston can lead to decreased combustion efficiency, higher emissions, and piston damage due to thermal loading. Modern high-speed diesel engines utilize high pressure common-rail direct-injection systems to primarily improve efficiency and reduce emissions. However, the high injection pressures of these systems increase the likelihood that the injected fuel will impinge on the surface of the piston.

A 2-dimensional numerical model (MTU-FILTER) for a single channel of a honeycomb ceramic diesel particulate trap has been developed. The mathematical modeling of the filtration, flow, heat transfer and regeneration behavior of the particulate trap is described. Numerical results for the pressure drop and particulate mass were compared with existing experimental results. Parametric studies of the diesel particulate trap were carried out. The effects of trap size and inlet temperature on the trap performance are studied using the trap model. An approximate 2-dimensional analytical solution to the simplified Navier-Stokes equations was used to calculate the velocity field of the exhaust flow in the inlet and outlet channels. Assuming a similarity velocity profile in the channels, the 2-dimensional Navier-Stokes equations are approximated by 1-dimenisonal conservation equations, which is similar to those first developed by Bissett.

An analysis of vehicle engine cooling airflow by means of a one-dimensional, transient, compressible flow model was carried out and revealed that similarity theory could be applied to investigate the variation of the airflow with ambient and operating conditions. It was recognized that for a given vehicle engine cooling system, the cooling airflow behavior could be explained using several dimensionless parameters that involve the vehicle speed, fan speed, heat transfer rate through the radiator, ambient temperature and pressure, and the system characteristic dimension. Using the flow resistance and fan characteristics measured from a prototype cooling system and the computer simulation for the one-dimensional compressible flow model, a quantitative correlation of non-dimensional mass flow rate to three dimensionless parameters for a prototype heavy-duty truck was established. The results are presented in charts, tables, and formulas.

A one-dimensional incompressible flow model covering the mechanisms involved in the airflow through an automotive radiator-shroud-fan system with no heat transfer was developed. An analytical expression to approximate the experimentally determined fan performance characteristics was used in conjunction with an analytical approach for this simplified cooling airflow model, and the solution is discussed with illustrations. A major result of this model is a closed form equation relating the transient velocity of the air to the vehicle speed, pressure rise characteristics and speed of the fan, as well as the dimensions and resistance of the radiator. This provides a basis for calculating cooling airflow rate under various conditions. The results of the incompressible flow analysis were further compared with the computational results obtained with a previously developed one-dimensional, transient, compressible flow model.