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Computer simulation was used as a complement to crash and injury field data analysis and physical sled and barrier tests to investigate and predict the spinal injuries of a rear impact in an IndyCar. The model was expected to relate the spinal loads to the observed injuries, thereby predicting the probability and location of spinal fractures. The final goal is to help reduce the fracture risk by optimizing the seat and restraint system design and the driver's position using computer modeling and sled testing. MADYMO Full FE Human Body Model (HBM) was selected for use because of its full spinal structural details and its compatibility with the vehicle and restraint system models. However, the IndyCar application imposed unique challenges to the HBM. First, the driver position in a race car is very different from that in a typical passenger car.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Automotive rollover is a complex mechanical phenomenon. In order to understand the mechanism of rollover and develop any potential countermeasures for occupant protection, efficient and repeatable laboratory tests are necessary. However, these tests are not well understood and are still an active area of research interest. It is not always easy or intuitive to estimate the necessary initial and boundary conditions for such tests to assure repeatability. This task can be even more challenging when rollover is a second or third event (e.g. frontal impact followed by a rollover). In addition, often vehicle and occupant kinematics need to be estimated a-priori, first for the safe operation of the crew and equipment safety, and second for capturing and recording the event. It is important to achieve the required vehicle kinematics in an efficient manner and thus reduce repetitive tests. Mathematical modeling of the phenomenon can greatly assist in understanding such kinematics.

The work presented here outlines the development of a robust CAO tool for optimal design of electromagnetic retarder machines. The developed EM-CAO tool is then used to perform a wide variety of CAE/CAO tasks, from automatically computing the torque versus rpm performance curves of the EM retarder to performing optimization. Two specific examples of optimal design of the EM retarder are reported. Through the use of a task manager/optimizer repetitive jobs are fully automated thereby making the analysis and optimization of electromagnetic retarders faster and user-friendlier.

The increasing power requirement for automotive electronics (radios, etc.), combined with ever-shrinking size and weight allowances, is creating a greater need for optimization and robust design of heat sinks. Not only does a heat sink directly affect the overall performance and reliability of a specific electronics application, but a well-designed, optimized heat sink can have other benefits - such as eliminating the requirement for special fans, reducing weight of the application, eliminating additional heat sink support structures, etc. Optimizing heat sink efficiency and thermal performance offers a challenge, due to the many competing design requirements. These requirements include effecting greater temperature reductions, accommodating vehicle packaging requirements and size limitations, generating a uniform heat distribution, etc., and all the while reducing the heat sink cost.

The starter drive clutch is a one way roller clutch and a key component in a starter motor that is used to crank internal combustion engines. The starter drive clutch transmits torque from an electrical motor to a ring gear mounted on a cranking shaft in an engine thus cranks the engine. The clutch also prevents the whole starter from damage caused by extremely high load and/or extremely high speed applied to the starter pinion from the engine. Drive slippage and barrel cracking are two major failure modes for the starter drive[1]. Insufficient torque capacity results in drive slippage while excessive high hoop stress on the clutch barrel ring causes barrel crack. To eliminate drive slippage failure, the clutch should be designed with high torque capacity. High torque capacity, however, is a cause of high hoop stress on the barrel that may result in the cracked barrel failure. Higher torque capacity and lower hoop stress are two completely opposite design directions.

This paper presents an unambiguous and intuitive method for identification of steering column resonant (SCR) mode of vibration. One simple but overlooked technique to determine the SCR mode in-vehicle is to provide local stiffnesses of the body locations where the Instrument Panel (IP) attaches, to the IP suppliers to be used in their design and development. This paper describes how this technique is useful in predicting the first few important in-vehicle steering column modes for different classes of vehicles, with examples presented in each class. The results obtained from such analyses are compared against those from direct in-buck simulations. This technique is not limited to its application in developing IP systems, but can easily be extended to include other systems such as seats, fuel tanks, etc. Also it is shown that a design optimization analysis may be performed using these attachment stiffnesses as design variables resulting in a system level solution.

Automotive gear oil development has expanded beyond the historical requirements of emphasizing wear protection to encompass modern needs for fuel economy and limited slip frictional properties. This paper describes the development process of a new generation, fuel efficient gear lubricant for use in light duty vehicles. A systematic formulation approach was used, encompassing fluid viscometrics and additive optimization. Performance testing in both laboratory and vehicle tests is described. Though standard GL-5 tests were used to confirm oxidation, wear and corrosion performance, emphasis is given to those methods used for optimizing fuel economy.

Customer clinics and surveys have revealed the increased importance to the customer of good defrost and demist performance in their vehicle. Achieving this level of performance, within the time and cost constraints of a modern vehicle development program, places increased reliance on computational (CAE) techniques. However, this paper describes how the optimum development process should be to combine this reliance upon CAE methods with a newly developed experimental technique. This new laser Doppler velocimetry (LDV) based methodology is employed at all stages of the development process and complements the CAE techniques perfectly. The end result is optimized airflow management within the vehicle cabin – essential if good defrost and demist performance is to be achieved in a vehicle.

The process for accurately estimating product reliability early in the development process can be a difficult and costly task. Traditional methods like Reliability Prediction Models and Life Testing Strategies yield beneficial results when relative information is known about the product that is to be analyzed. When there is minimal information known (prior failure rates…) such a new concept design these above reliability methods have limitations. For these cases a Virtual Testing Strategies have proven to yield valuable results. This paper will demonstrate a reliability analysis procedure for a new automotive concept design. This analysis procedure composes of a mathematical model, model validation, parameter diagram, design of experiment (DOE), response surface, and optimization.

Evolutionary Operation (EVOP) experimental design using Sequential Simplex method is an effective and robust means for determining the ideal process parameter (factor) settings to achieve optimum output (response) results. EVOP is the methodology of using on-line experimental design. Small perturbations to the process are made within allowable control plan limits, to minimize any product quality issues while obtaining information for improvement on the process. It is often the case in high volume production where issues exist, however off-line experimentation is not an option due to production time, the threat of quality issues and costs. EVOP leverages production time to arrive at the optimum solution while continuing to process saleable product, thus substantially reducing the cost of the analysis.

Analytical methods are used extensively in the automotive industry to validate the feasibility of component and assembly designs and their dynamic behavior. Correlation of analytical models with test data is an important step in this process. This paper discusses the Finite Element model of an innovative Slip-in-Tube Propshaft design. The Slip-in-Tube joint (slip joint) poses challenges for its dynamic simulation. This paper discusses the methods of simulating the joint and correlating it to experimental results. Also, the Noise and Vibration (NVH) characteristics of the Slip-in-Tube Propshaft design. In this paper, a Finite Element model of the proposed propshaft is developed using shell and beam element formulations. Each model is verified to optimize the feasibility of using accurate and computationally efficient elements for the dynamic analysis.

An integrated optimization system has been developed to combine optimization algorithms with Finite Element Analysis for airbag design. A number of industry standard software packages are employed to work in coherence to complete the optimization procedure automatically with minimal user intervention. The system can be easily tailored to fit multiple performance requirements and various design constraints for different airbag systems. Compared with the commonly used Design of Experiment (DOE) method, time and computer resources requirements are greatly curtailed. The integrated optimization system was successfully used in single-chamber and dual-chamber airbag optimizations. The results proved the effectiveness of the system and demonstrated its capability in product design.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and optimization of a hydraulic steering pump for NVH performance. DOE methods were applied to RPM-domain data to examine the effect of several different factors, as well as the interactions between these factors, on pump NVH. Whereas most DOE analyses typically consider only a single response variable, the present work considered multiple response variables. Specifically, pump NVH performance curves for several pump rotational orders over a range of shaft speeds were analyzed. Thus, it was possible to determine the effect of the factors in question over the entire speed range of pump operation, rather than a single speed or setting. Statistical methods were applied to determine which factors and interactions had a significant effect on pump NVH. These factors were used to construct an empirical mathematical prediction model for NVH performance.

Robust Engineering techniques developed by Taguchi have traditionally applied to the optimization of engineering designs. Robust Engineering methods also may be applied to software testing of ECU algorithms. The net result is an approach capable of improving the software algorithm in one of two ways. First the approach can identify the range of areas which prove problematic to the software such that a robust solution may be developed. Conversely, the approach can be used as a general strategy to verify that the software is robust over the range of inputs tested. The robust engineering methods applied to software testing utilize orthogonal array experiments to test software over a range of inputs. The actual software trials are best performed in the simulation environment and also via automated test hardware in the loop configurations in realtime. This paper outlines a process for applying Robust Engineering methods to software testing.

A new optimal control strategy for dealing with braking actuator failures in a vehicle equipped with a brake-by-wire and steer-by- wire system is described. The main objective of the control algorithm during the failure mode is to redistribute the control tasks to the functioning actuators, so that the vehicle performance remains as close as possible to the desired performance in spite of a failure. The desired motion of the vehicle in the yaw plane is determined using driver steering and braking inputs along with vehicle speed. For the purpose of synthesizing the control algorithm, a non-linear vehicle model is developed, which describes the vehicle dynamics in the yaw plane in both linear and non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints.

Rising costs continue to be a problem within the automotive industry. One way to address these rising costs is through modularity. Modular systems provide the ability to achieve product variety through the combination and standardization of components. Modular design approaches used in development of vehicle electrical, electronic, and software (EES) systems allow sharing of architectures/modules between different product lines (vehicles). This modular design approach may provide economies of scale, reduced development time, reduced order lead-time, easier product diagnostics, maintenance and repair. Other benefits of this design approach include development of a variety of EES systems through component swapping and component sharing. In this paper, new optimization algorithms and software tools are presented that allow vehicle EES system design engineers to develop modular architectures/modules that can be shared across vehicle platforms (for OEMs) and across OEMs (for suppliers).

Active/semi-active suspension control of a passenger vehicle is a classic problem involving multiple-objectives, all of which cannot be simultaneously achieved without compromises between ride and handling performance. Traditionally, suspension control tuning has been a subjective process that involves tuning of hundreds of parameters. This paper attempts to add some level of objectivity to the tuning philosophy by posing the ride/handling trade-off as a multi-constrained, multi-objective optimization problem and solving it using a mixed-H2/H∞ control synthesis technique to obtain a pareto-optimal solution. The multi-variable constrained optimization problem involves minimization of body control metrics subject to constraints defined by wheel-control metrics (a measure of road-holding capability). Simulation as well as road-test results clearly demonstrate the effectiveness and impact the proposed control strategy has on improving ride and handling performance.

Close-coupled or manifold catalysts have been extensively employed to reduce emissions during cold start by achieving quick catalyst light-off. These catalysts must have good thermal durability, high intrinsic light-off activity and high HC/CO/NOx conversions at high temperature and flow conditions. A number of studies have been dedicated to engine control, manifold design and converter optimization to reduce cold start emissions. The current paper focuses on the effect of catalyst design parameters and their performance response to different engine operating conditions. Key design parameters such as catalyst formulation (CeO2 vs. non CeO2), precious metal loading and composition (Pd vs. Pd/Rh), washcoat loading, catalyst thermal mass, substrate properties and key application (in use) parameters such as catalyst aging, exhaust A/F ratio, A/F ratio modulation, exhaust temperature, temperature rise rate and exhaust flow rate were studied on engine dynamometers in a systematic manner.

Although not completely understood, rotor distortion due to bolt-up is an issue commonly found in conventional brake rotor design. In this paper, bolt-up is addressed by utilizing optimization and contact analysis methods. These methods give greater insight to the contributing factors that influence bolt-up distortion. In particular, the optimization method defines the approximate geometric shape required for a brake rotor based on optimizing one or more variables. By utilizing the non-linear contact analysis method, the results from the optimization analysis are validated. In general, the results show that bolt-up distortion is not significantly affected by changing design features, variables or combinations of design features and variables. However, significant improvement in bolt-up distortion is noticed when changes are made to the brake rotor and the wheel bearing hub.