Search Results

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.

An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers.

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.

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].

This paper explores the trade-off between reliability-based design and robustness for an automotive under-hood thermal system using the iSIGHT-FD environment. The interaction between the engine cooling system and the heating, ventilating, and air-conditioning (HVAC) system is described. The engine cooling system performance is modeled using Flowmaster and a metamodel is developed in iSIGHT. The actual HVAC system performance is characterized using test bench data. A design of experiment procedure determines the dominant factors and the statistics of the HVAC performance is obtained using Monte Carlo simulation (MCS). The MCS results are used to build an overall system response metamodel in order to reduce the computational effort. A multi-objective optimization in iSIGHT maximizes the system mean performance and simultaneously minimizes its standard deviation subject to probabilistic constraints.

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.

Physical modeling has been used by the industry to improve development time and produce a quality product. In this paper, we will describe two methods used in system control to take advantage of the physical model. One method describes a complete transmission physical model with a full system control utilizing co-simulation techniques. Data will be presented, and comparison to vehicle data will be conducted and verified. The second method will illustrate how to utilize the physical model to improve system design and modification. In this method, vehicle data will be used as inputs to the model, the model output will be verified against vehicle output data. The two methods are excellent tools for the Design For Six Sigma process (DFSS design).

With increased demand for improvements in the efficiency and operation of all automotive engine components, including those in the engine cooling system, there is a need to develop a set of virtual tools that can aid in both the evaluation and design of automotive components. In the case of automotive radiators, improvements are needed in the overall pressure drop as well as the coolant flow homogeneity across all radiator tubes. The latter criterion is particularly important in the reduction of premature fouling and failure of heat exchangers. Rather than relying on ad hoc geometry changes with the goal of improving the performance of radiators, the coupling of CFD flow simulations with numerical shape optimization methods could assist in the design and testing of automotive heating and cooling components.

Environmental concerns and government regulations are factors that have led to an increased focus on fuel economy in the automotive industry. This paper identifies a method used to improve the efficiency of a front-wheel-drive (FWD) automatic transmission. In order to create improvements in large complex systems, it is key to have a large scope, to include as much of the system as possible. The approach taken in this work was to use Design for Six Sigma (DFSS) methodology. This was done to optimize as many of the front-wheel-drive transmission components as possible to increase robustness and efficiency. A focus of robustness, or consistency in torque transformation, is as important as the value of efficiency itself, because of the huge range of usage conditions. Therefore, it was necessary to find a solution of the best transmission component settings that would not depend on specific usage conditions such as temperatures, system pressures, or gear ratio.

The sound quality of a prototype series hydraulic hybrid passenger vehicle powertrain was analyzed. Different sound quality metrics were evaluated to determine which one correlated best with the subjective assessment of sound quality, and a desired sound quality target was developed. Next, the effect of the design of the hydraulic powertrain components on sound quality was analyzed. Two extreme options were analyzed: “stiff” systems with a hard drive shaft or short fluid hoses, and “soft” systems with a soft drive shaft or long fluid hoses. Experimental results from these systems are presented in the paper. Finally, design recommendations were made to achieve the best sound quality of the hybrid hydraulic powertrain, and therefore maximum customer satisfaction.

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.

Improvements in the pressure drop across and flow homogeneity in the tubes of automotive radiators are needed to reduce the power demands on the vehicle water pump and increase the lifetime of the radiator. The goal of this ongoing work is to develop a set of virtual tools coupling CFD flow simulations with numerical shape optimization methods to assist in the design and testing process of automotive heating and cooling components. In SAE paper 2002-01-0952, “Towards Shape Optimization of Radiator Cooling Tanks,” the authors developed and evaluated optimization criteria for pressure drop and mass flow rate distribution in a water-to-air automotive heat exchanger. In this follow-up paper, results based on the implementation of these optimization criteria are presented. More specifically, results concerning the placement of radiator inlets and outlets are addressed.

Brake judder is a brake induced vibration that a vehicle driver experiences in the steering wheel or floor panel at highway speeds during vehicle deceleration. The primary cause of this disturbance phenomenon is the brake torque variation (BTV). Virtual CAE tools from both kinematics and compliance standpoints have been applied in analyzing sensitivities of the vehicle systems to BTV. This paper presents a recently developed analytical approach that identifies parameters of steering and suspension systems for achieving optimal settings that desensitize the vehicle response to BTV. The analytical steps of this integrated approach started with creating a lumped mass noise-vibration-harshness (NVH) control model and a separate multi-body dynamics (MBD) suspension model. Then, both models were linked to run in a sequence through optimization software so the results from the MBD model were used as quasi-static inputs to the lumped mass NVH model.

Spot Welding is now widely used in the fabrication of sheet metals, mainly due to the cost and time considerations. Spot welds are found in nearly all products where sheet metal is joined. Examples range from a single metal toolbox to nearly 10,000 spot welds found in a typical passenger car. Obviously the quality of the spot weld has a direct impact on the quality of the product. The problem of estimating the spot-weld quality is an important component in quality control. If the weld nuggets are improperly or incompletely formed, or the area surrounding the nugget is smaller than required, the structural integrity of the entire part may be uncertain. Furthermore these inconsistencies are usually internal and are seldom visible to Optical Inspection. This study is focused on the non-destructive evaluation of the spot welds using “Digital Shearography”.

An automotive vehicle should be designed to satisfy the wants of customers. The key is how to convert voices of customers into engineering languages. In other words, transfer the wants of customers into the right technical characteristics of a vehicle. A questionnaire of customer wants for a CUV (Crossover Utility Vehicle) is created and processed. Using QFD (Quality Function Deployment) and modified KANO model, the relative important degree is obtained from the original relative important degree of customer wants surveyed. Since some information gained is uncertain and the questionnaire sample is limited, a gray correlation analysis method is introduced, which calculates the competitive important degree of customer wants, then the final important degree of customer wants is gained by integrating the relative important degree and the competitive important degree.

Passengers' frequent requests are for less Noise, Vibration and Harshness (NVH) in the vehicle compartment. This and the reduction of noise and vibration levels from major sources like the engine necessitate better performance of other sources of noise and vibrations in a vehicle. Some of these sources are the hydraulic circuits including the power steering system. Fluid pulses or pressure ripples, generated typically by a pump, become excitation forces to the structure of a vehicle or the steering gear and represent a considerable source of discomfort to the vehicle passengers. Current power steering technology attenuates this ripple along the pressure line connecting the pump to the steering gear. Finding the optimum design configuration for the components (hose, tuner, tube, and others) has been a matter of experience-based trial and error. This paper is a part of a program to simulate and optimize fluid borne noise in hydraulic circuits.