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The ride performance potentials of a prototype torsio-elastic axle suspension for an off-road vehicle were investigated analytically and experimentally. A forestry vehicle was fitted with the prototype suspension at its rear axle to assess its ride performance benefits. Field measurements of ride vibration along the vertical, lateral, fore-aft, roll and pitch axes were performed for the suspended and an unsuspended vehicle, while traversing a forestry terrain. The measured vibration responses of both vehicles were evaluated in terms of unweighted and frequency-weighted rms accelerations and the acceleration spectra, and compared to assess the potential performance benefits of the proposed suspension. The results revealed that the proposed suspension could yield significant reductions in the vibration magnitudes transmitted to the operator's station.

Superior NVH performance is a key focus in the development of new powertrains. In recent years, computer simulations have gained an increasing role in the design, development, and optimization of powertrain NVH at component and system levels. This paper presents the results of a study carried out on a 4-cylinder in-line spark-ignition engine with focus on growl noise. Growl is a low frequency noise (300-700 Hz) which is primarily perceived at moderate engine speeds (2000-3000 rpm) and light to moderate throttle tip-ins. For this purpose, a coupled and fully flexible multi-body dynamics model of the powertrain was developed. Structural components were reduced using component mode synthesis and used to determine dynamics loads at various engine speeds and loading conditions. A comparative NVH assessment of various crankshaft designs, engine configurations, and in- cylinder gas pressures was carried out.

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.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

Accurate numerical prediction of an engine thermal map at a wide range of engine operating conditions can help tune engine performance parameters at an early development stage. This study documents the correlation of an engine thermal simulation using the conjugate heat transfer (CHT) methodology with thermocouple data from an engine operating in a dynamometer and a vehicle drive cell. Three different operating conditions are matched with the simulation data. Temperatures predicted by simulation at specific sections, both at the intake and the exhaust sides of the engine are compared with the measured temperatures in the same location on the operating engine.

The number of software-intensive and complex electronic automotive systems is continuously increasing. Many of these systems are safety-critical and pose growing safety-related concerns. ISO 26262 is the automotive functional safety standard developed for the passenger car industry. It provides guidelines to reduce and control the risk associated with safety-critical systems that include electric and (programmable) electronic parts. The standard uses the concept of Automotive Safety Integrity Levels (ASILs) to decompose and allocate safety requirements of different stringencies to the elements of a system architecture in a top-down manner: ASILs are assigned to system-level hazards, and then they are iteratively decomposed and allocated to relevant subsystems and components. ASIL decomposition rules may give rise to multiple alternative allocations, leading to an optimization problem of finding the cost-optimal allocations.

A body mount joint is a typical clamped joint that is under severe loading conditions, due to its structural function services as a gateway of load path between body and frame of an automotive vehicle. Stresses/strains on durability concerned components at the joint cannot be captured accurately by using the pseudo stress analysis approach because of the complexity of stress state generated by the pre-stress from clamp load, contacts between the components and nonlinear material properties. In this paper, development of a technique for fatigue life estimation of the joint is described in detail.

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.

This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

This paper introduces a methodology to calculate confidence bounds for a normal and Weibull distribution using Monte Carlo pivotal statistics. As an example, a ready-to-use lookup table to calculate one-sided lower confidence bounds is established and demonstrated for normal and Weibull distributions. The concept of one-sided lower tolerance limits for a normal distribution was first introduced by G. J. Lieberman in 1958 (later modified by Link in 1985 and Wei in 2012), and has been widely used in the automotive industry because of the easy-to-use lookup tables. Monte Carlo simulation methods presented here are more accurate as they eliminate assumptions and approximations inherent in existing approaches by using random experiments. This developed methodology can be used to generate confidence bounds for any parametric distribution. The ready-to-use table for the one-sided lower tolerance limits for a Weibull distribution is presented.

A two-passenger, all-wheel-drive urban electric vehicle (AUTO21EV) with four direct-drive in-wheel motors has been designed and developed at the University of Waterloo. An advanced genetic-fuzzy active steering controller is developed based on this vehicle platform. The rule base of the fuzzy controller is developed from expert knowledge, and a multi-criteria genetic algorithm is used to optimize the parameters of the fuzzy active steering controller. To evaluate the performance of this controller, a computational model of the AUTO21EV is driven through several standard test maneuvers using an advanced path-following driver model. As the final step in the evaluation process, the genetic-fuzzy active steering controller is implemented in a hardware- and operator-in-the-loop driving simulator to confirm its performance and effectiveness.

A two-passenger, all-wheel-drive urban electric vehicle (AUTO21EV) with four direct-drive in-wheel motors has been designed and developed at the University of Waterloo. A 14-degree-of-freedom model of this vehicle has been used to develop a genetic fuzzy yaw moment controller. The genetic fuzzy yaw moment controller determines the corrective yaw moment that is required to stabilize the vehicle, and applies a virtual yaw moment around the vertical axis of the vehicle. In this work, an advanced torque vectoring controller is developed, the objective of which is to generate the required corrective yaw moment through the torque intervention of the individual in-wheel motors, stabilizing the vehicle during both normal and emergency driving maneuvers. Novel algorithms are developed for the left-to-right torque vectoring control on each axle and for the front-to-rear torque vectoring distribution action.

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].

Torsional vibration dampers are used in automatic and manual transmissions to provide passenger comfort and reduce damage to transmission & driveline components from engine torsionals. This paper will introduce a systematic method to model a torque converter (TC) arc spring damper system using Simdrive software. Arc spring design parameters, dynamometer (dyno) setup, and complete powertrain/driveline system modeling and simulation are presented. Through arc spring dynamometer setup subsystem modeling, the static and dynamic stiffness and hysteresis under different engine loads and engine speeds can be obtained. The arc spring subsystem model can be embedded into a complete powertrain/driveline model from engine to wheels. Such a model can be used to perform the torsional analysis and get the torsional response at any location within the powertrain/driveline system. The new methodology enables evaluation of the TC damper design changes to meet the requirements.

During the vehicle development process, dimensional variation simulation modeling has been applied extensively to estimate the effects of build variation on the final product. Traditional variation simulation methods analyze the tolerance inputs of structural components, but do not account for any compliance effects due to stiffness variation in tuning components, such as bushings, springs, isolators, etc., since both product and process variation are simulated based on rigid-body assumptions. Vehicle performance objectives such as ride and handling (R&H) often involve these compliance metrics. The objective of this paper is to present a method to concurrently simulate the tolerance from the structural parts as well as the variability of compliance from the tuning components through an integration package. The combination of these two highly influential effects will allow for a more accurate prediction and assessment of vehicle performance.

The design for manufacturability process has been recognized as a very effective method for improving the overall quality in mechanical product design. The first part of the paper deals with an extended DFM which encompasses all the various Quality issues in product development. The importance of the three major elements quality, cost and timing are highlighted in the mathematical model for Design for Quality (DFQ). The second part of the paper describes the application of DFQ in the design and development of minivan body and interior systems. The best value of the DFQ is recognized when the process is used proactively during the early stages of the development cycle. Such is the case of the applications discussed in this paper which covers the following systems: hood assembly, seamless door system, sliding door system, instrument panel and message center installation, and fuel filler door-and-housing system.

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.