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In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.

Fatigue analysis in the time domain using the rainflow cycle counting algorithm is considered the most accurate method for estimating damage. Dirlik's method has been found to be very accurate for damage estimation in the frequency domain. Previous studies have demonstrated the usefulness of Dirlik's method for ocean engineering and wind turbines but few have shown how well Dirlik performs in automotive applications. This study compares Dirlik's method with the rainflow cycle counting and with other frequency domain methods. The study analyzes measured data for an automotive component subjected to five test track load conditions. In addition, fourteen of Dirlik's original spectra and seven additional spectra which combine sine and random spectra are studied. It was found that Dirlik's method predicts more damage than the rainflow cycle counting method when applied to the original data used in creating the method.

In this paper, a transient thermal analysis model for Diesel fuel systems is presented. The purpose of this work is to determine the fuel temperature at various locations along the system, especially inside the tank and at the returned fuel inlet to the tank. Due to the fact that the fuel level is continuously changing during any driving condition, the fuel mass inside the tank is also continuously changing. Consequently, the fuel temperature will change even under steady driving or idle conditions, therefore, this problem should be analyzed using transient thermal analysis models. Effective thermal management requires controlling the surface temperature of the fuel tank, fuel lines and the fuel temperature at the fuel return line as well as inside the tank [1, 2]. Based on the thermal analysis results, it is possible to determine the major source of heat input at several locations of the fuel system.

Two on-line algorithms have been developed to acquire driveline component loads in terms of revolutions at torque and rainflow cycle counting matrix. These algorithms have been implemented in real-time on a standard engine controller unit and have been optimized for fast run-time and low memory requirements. The revolutions at torque algorithm is intended to count the number of driveshaft revolutions in each torque level for each gear and store the number of counts in the engine controller memory. The rainflow cycle counting algorithm is intended to count driveshaft torque cycles and to store the number of counts in a two dimensional “from-to” matrix format in the engine controller memory. The revolutions at torque histogram data and the rainflow cycle counting matrix are then downloaded from the vehicle using the data collection device. Download occurs when the vehicle is serviced at a dealership.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

In an environment of tougher engineering constraints to deliver tomorrow's aerodynamic vehicles, evaluation of aerodynamics early in the design process using digital prototypes and simulation tools has become more crucial for meeting cost and performance targets. Engineering needs have increased the demands on simulation software to provide robust solutions under a range of operating conditions and with detailed geometry representation. In this paper the application of simulation tools to wheel design in on-road operating conditions is explored. Typically, wheel and wheel cover design is investigated using physical tests very late in the development process, and requires costly testing of many sets of wheels in an on-road testing environment (either coast-down testing or a moving-ground wind-tunnel).

A process to create a vehicle resistance curve based on airflow predictions using Computational Fluid Dynamics (CFD) simulation technique is presented. 1-dimensional engine cooling system simulation tool KULI is used to compute the coefficients of vehicle resistance curve. A full factorial Design of Experiment (DOE) established the relationship between the coefficients and the sum of absolute difference between KULI and CFD predictions. The NLPQL optimization routine is used to accurately predict the coefficients so that sum of absolute difference between KULI and CFD predictions is minimized.

One method of reducing the number and/or severity of vehicle crashes is to warn the driver of a potential crash. The theory is that there will be driving conditions in which the drivers are unaware of a potential crash and a warning system will allow them to, in some manner, avoid the accident or reduce the severity. In an attempt to develop an analytical understanding of Forward Collision Warning systems (FCW) for frontal impacts a 2-d mathematical/kinematic model representing a set of pre-crash vehicle dynamic maneuvers has been built. Different driving scenarios are studied to explore the potential improvement of warning algorithms in terms of headway reduction and minimization of false alarm rates. The results agree with the field data. NHTSA's new NCAP active safety criteria are evaluated using the model. The result from the analysis indicates that the NHTSA criteria may drive higher false alarm rates. Opportunities of minimizing false positive rates are discussed.

Establishing data adjustments that will give an interference free result for bluff bodies in automotive wind tunnels has been pursued for at least the last 45 years. Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap on the performance of the two-measurement technique. The subject CFD studies are designed to eliminate all wind tunnel interference effects except for the variation of the (linear) static pressure gradient.

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

Using gasoline and diesel simultaneously in a dual-fuel combustion system has shown effective benefits in terms of both brake thermal efficiency and exhaust emissions. In this study, the dual-fuel approach is applied to a light-duty spark ignition (SI) gasoline direct injection (GDI) engine. Three combustion modes are proposed based on the engine load, diesel micro-pilot (DMP) combustion at high load, SI combustion at low load, and diesel assisted spark-ignition (DASI) combustion in the transition zone. Major focus is put on the DMP mode, where the diesel fuel acts as an enhancer for ignition and combustion of the mixture of gasoline, air, and recirculated exhaust gas. Computational fluid dynamics (CFD) is used to simulate the dual-fuel combustion with the final goal of supporting the comprehensive optimization of the main engine parameters.

With the advent of quieter powertrain and improved cabin acoustic sealing, there is an increased focus on noise generated in the HVAC unit and climate control ducting system. With improved insulation from exterior noise sources such as wind & road noise, HVAC noise is more perceptible by the occupants and is a key quality indicator for new generation vehicles. This has increased the use of simulations tools to predict HVAC noise during the virtual development phase of new vehicle programs. With packaging space being premium under the instrument panel, changes to address noise issues are expensive and often impractical. The current methodology includes the best practices in simulation accumulated from prior aero acoustics validation studies on fans, ducts, flaps and plenum volume discharge. The paper details the acoustic noise generation and propagation in the near field downstream of an automotive HVAC unit in conjunction with ducting system.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.

This paper presents the design of a hybrid powertrain damping control algorithm using the sliding mode control (SMC) scheme. Motor control-based active damping control strategy is used to ensure smooth drive line operation and provide the driver with seamless driving experience. In the case of active damping control, motor and engine speeds are measured to monitor the driveline state, and corrective motor torques are generated to dampen out drive line vibrations. Drive lines are prone to internal vibration (engine, clutches and motors) as well as external disturbances caused by road inputs. As such, fast-response actuator-based damping control systems are desirable in a hybrid powertrain application, where a torque converter is generally not used. The most significant aspect of an active damping control algorithm is the error calculation, based on proper states information, and torque determination based on the adaptive control gain applied to the nonlinear system.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap and add more realistic model and wind tunnel conditions to the evaluations of the performance of the two-measurement technique. The subject CFD studies are designed to greatly reduce all wind tunnel interference effects except for the variation of the non-linear static pressure gradients. A zero gradient condition is generated by simulating a solid wall test section with a blockage ratio of 0.1%.

Computational tools have been extensively applied to predict component temperatures before an actual vehicle is built for testing [1, 2, 3, 4, and 5]. This approach provides an estimate of component temperatures during a specific driving condition. The predicted component temperature is compared against acceptable temperature limits. If violations of the temperature limits are predicted, corrective actions will be applied. These corrective actions may include adding heat shields to the heat source or to the receiving components. Therefore, design changes are implemented based on the simulation results. Sensitivity analysis is the formal technique of determining most influential parameters in a system that affects its performance. Uncertainty analysis is the process of evaluating the deviation of the design from its intended design target.

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.

Generic spindle loads are used in the upfront analysis for vehicle durability development. They represent different load case into the vehicle suspension system, such as potholes, cornering, and braking. The advantage of using these generic load cases is that they can be used upfront in the durability development process before hardware is available. The generic spindle loads are cascaded through the suspension system to generate component loads which can then be used for stress analysis. The paper describes a study that was done to determine the validity of current generic spindle loads by analyzing spindle data from multiple vehicles in the same class. The paper will explain the initial data analysis that was done, which was normalizing the spindle loads by weight. In addition, the paper will then go into further detail on describing a relationship between spindle loads and tire sidewall height, which reduced the load scatter.