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An optimal idle speed control (ISC) system for an automotive engine is introduced in this paper. The system is based on a non-linear model including time delay. This model is linearized at the nominal operating point. The effect of the time delay on control is compensated by prediction. This methodology is applied to a Chrysler 2.0 liter 4-cylinder SOHC (Single Overhead Cam) engine. All of the unknown parameters of the model are identified by using the normal operating data from the test engine. Based on these identified parameters, an optimal controller was designed and implemented using a rapid prototyping system. Numerous experiments of the optimal controller were carried out at the Chrysler Technology Center in Auburn Hills, Michigan. The performance was compared to that of the existing controller. The results showed that the optimal controller has the capability to effectively control the engine idle speed under a variety of accessory loads and disturbances.

The concept of a new finite element analysis methodology to solve vehicle system NVH problems is proposed. The approach is non-conventional in the sense that, instead of NASTRAN type implicit finite element code, the explicit nonlinear dynamic code LS-DYNA is used to conduct the time domain analysis and the FFT is then used to conduct the frequency domain analysis. The advantages of this new approach include the ability to consider material and structural nonlinearity, damping and contact interface between parts, as well as the potential of expand the frequency envelop up above 200 Hz. The main disadvantage of this method is the computing CPU time required which will become less and less important as computer speed becomes faster and faster at an increased pace. Examples of normal modes for rectangular plate, tire/wheel system, and chassis subframe are presented to illustrate the method and comparisons with results from other methods are also given whenever possible.

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.

One-dimensional (1D) engine simulation packages are limited in modeling flows through an adverse pressure gradient where boundary layer separation is more likely to occur, as in the case of the diffuser part of the restrictor. The restrictor modeling difficulty usually manifests itself as an engine model that consumes a lot of effort (both computational and from the user) in the modeling of the restrictor. The approach sought in this work was to provide a flow vs pressure drop dependency to the code such that it does not consume too much effort in the analysis of the restrictor. This approach is similar to that used for the valve flow, where a look up table is typically provided for determining the flow. Experimentally determined flow measurements on a thin-plate orifice, a short restrictor and a long restrictor are presented and discussed. The developed model gave excellent results in an acyclic steady-state simulation and is being integrated in the full engine model.

This study examines the contributions and interactions of intake and exhaust tuning on a 4-stroke single-cylinder engine for various engine speeds and valve timings. The parametric study was performed using a 1-D engine simulation model, the combustion sub-model of which was calibrated based on experimental pressure data. Mechanisms by which tuning changes the volumetric efficiency of an engine were studied. Simulation results are compared with established empirical correlations which predict pipe lengths for maximum volumetric efficiency. It was found that intake tuning has a more dominant role in the breathing capability of the engine compared to exhaust tuning and that both are independent from each other. Valve timing was found to have no effect on intake tuning characteristics but to affect exhaust tuning.

Production software validation is critical during software development, allowing potential quality issues that could occur in the field to be minimized. By developing automated and repeatable software test methods, test cases can be created to validate targeted areas of the control software for confirmation of the expected results from software release to release. This is especially important when algorithm/software development timing is aggressive and the management of development activities in a global work environment requires high quality, and timely test results. This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The powertrain model used within the HIL consists of an engine model and a detailed automatic transmission dynamics model. The model runs in an OPAL-RT TestDrive based HIL system.

This paper describes a new tool to capture cylinder pressure information, calculate combustion parameters, and implement control algorithms. There are numerous instrumentation and prototyping systems which can provide some or all of this capability. The Cylinder Pressure Development Controller (CPDC) is unique in that it uses advanced high volume automotive grade circuitry, packaging, and software methodologies. This approach provides insight regarding the implementation of cylinder pressure based controls in a production engine management system. A high performance data acquisition system is described along with a data reduction technique to minimize data processing requirements. The CPDC software architecture is discussed along with model-based algorithm development and autocoding. Finally, CPDC calculated combustion parameters are compared with those from a well established combustion analysis system and thermodynamic simulations.

A reliability analysis method is presented for time-dependent systems under uncertainty. A level-crossing problem is considered where the system fails if its maximum response exceeds a specified threshold. The proposed method uses a double-loop optimization algorithm. The inner loop calculates the maximum response in time for a given set of random variables, and transforms a time-dependent problem into a time-independent one. A time integration method is used to calculate the response at discrete times. For each sample function of the response random process, the maximum response is found using a global-local search method consisting of a genetic algorithm (GA), and a gradient-based optimizer. This dynamic response usually exhibits multiple peaks and crosses the allowable response level to form a set of complex limit states, which lead to multiple most probable points (MPPs).

An efficient approach for series system reliability-based design optimization (RBDO) is presented. The key idea is to apportion optimally the system reliability among the failure modes by considering the target values of the failure probabilities of the modes as design variables. Critical failure modes that contribute the most to the overall system reliability are identified. This paper proposes a computationally efficient, system RBDO approach using a single-loop method where the searches for the optimum design and for the most probable failure points proceed simultaneously. Specifically, at each iteration the optimizer uses approximated most probable failure points from the previous iteration to search for the optimum. A second-order Ditlevsen upper bound is used for the joint failure probability of failure modes. Also, an easy to implement active strategy set is employed to improve algorithmic stability.

Reliability-based design optimization accounts for variation. However, it assumes that statistical information is available in the form of fully defined probabilistic distributions. This is not true for a variety of engineering problems where uncertainty is usually given in terms of interval ranges. In this case, interval analysis or possibility theory can be used instead of probability theory. This paper shows how possibility theory can be used in design and presents a computationally efficient sequential optimization algorithm. The algorithm handles problems with only uncertain or a combination of random and uncertain design variables and parameters. It consists of a sequence of cycles composed of a deterministic design optimization followed by a set of worst-case reliability evaluation loops. A crank-slider mechanism example demonstrates the accuracy and efficiency of the proposed sequential algorithm.

Recently the use of digital 3D profilometry in the automotive industries has become increasingly popular. The effective techniques for 3D shape measurement, especially for the measurement of complicated structures, have become more and more significant. Different optical inspective methods, such as 3D profilometry, laser scanning and Coordinate-Measuring Machine (CMM), have been applied for 3D shape measurement. Among these methods, 3D profilometry seems to be the fastest and inexpensive method with considerably accurate result, and it has simple setup and full field measuring ability compared with other techniques. In this paper, a novel calibration method for 3D-profilometry will be introduced. In this method, a multiple-step calibration procedure is utilized and best-fit calibration curves are obtained to improve measurement accuracy. A recursive algorithm is used for data evaluation, along with calibration data.

Low vibration and noise level in internal combustion engines has become an essential part of the design process. It is well known that the piston assembly can be a major source of engine mechanical friction and cold start noise, if not designed properly. The piston secondary motion and piston-bore contact pattern are critical in piston design because they affect the skirt-to-bore impact force and therefore, how the piston impact excitation energy is damped, transmitted and eventually radiated from the engine structure as noise. An analytical method is presented in this paper for simulating piston secondary dynamics and piston-bore contact for an asymmetric half piston model. The method includes several important physical attributes such as bore distortion effects due to mechanical and thermal deformation, inertia loading, piston barrelity and ovality, piston flexibility and skirt-to-bore clearance. The method accounts for piston kinematics, rigid-body dynamics and flexibility.

Modern engines are becoming highly complex, with several strongly interactive subsystems - - variable cam phasers on both intake and exhaust, along with various kinds of variable valve lift mechanisms. Isolated component models may not yield adequate information to deal with system-level interactive issues, especially when it comes to transient behavior. In addition, massive amounts of expensive experimental work will be required for optimization. Recent computing speed improvements are beginning to permit the use of co-simulation to couple highly detailed and accurate submodels of the various engine components, each created using the most appropriate available simulation package. This paper describes such a system model using GT-Power to model the engine, AMESim to model cam phasers and the engine lubrication system, and Matlab/Simulink to model the engine controllers and the vehicle.

An analytical method is presented in this paper for simulating piston secondary dynamics and piston-bore contact for an asymmetric half piston model including elastohydrodynamic (EHD) lubrication at the bore-skirt interface. A piston EHD analysis is used based on a finite-difference formulation. The oil film is discretized using a two-dimensional mesh. For improved computational efficiency without loss of accuracy, the Reynolds’ equation is solved using a perturbation approach which utilizes an “influence zone” concept, and a successive over-relaxation solver. The analysis includes several important physical attributes such as bore distortion effects due to mechanical and thermal deformation, inertia loading and piston barrelity and ovality. A Newmark-Beta time integration scheme combined with a Newton-Raphson linearization, calculates the piston secondary motion.

The quality of engine lubrication depends upon how much oil is supplied and how the lubricant is pressurized to the lubricated components. These variables strongly affect the safe operation and lifespan of an engine. During the conceptual design stage of an engine, its lubrication system cannot be verified experimentally. It is highly desirable for design engineers to utilize computer simulations and robust design methodology in order to achieve their goal of optimizing the engine lubrication system. The heuristic design principle is a relatively routine resource for design engineers to pursue although it is time consuming and sacrifices valuable developing time. This paper introduces an unusual design methodology in which design engineers were involved in analyzing their own designs along with lubrication system analyst to establish a link between two sophisticated software packages.

High-fidelity finite element (FE) tire-snow interaction models have the advantage of better understanding the physics of the tire-snow system. They can be used to develop semi-analytical models for vehicle design as well as to design and interpret field test results. For off-terrain conditions, there is a high level of uncertainties inherent in the system. The FE models are computationally intensive even when uncertainties of the system are not taken into account. On the other hand, field tests of tire-snow interaction are very costly. In this paper, dynamic metamodels are established to interpret interaction forces from FE simulation and to predict those forces by using part of the FE data as training data and part as validation data. Two metamodels are built based upon the Krieging principle: one has principal component analysis (PCA) taken into account and the other does not.

Full nonlinear finite element radial-ply and bias-ply tire models are developed to investigate different structured tires' transmissibility phenomena. The reaction forces of the tire axles in time domain are recorded first when the tires encounter a bump (cleat), and then the FFT algorithm is applied to examine the dynamic response information in frequency domain. The results of the radial-ply vs. bias-ply tires' transmissibility are validated against previous studies and show reasonable agreement.

Traffic engineers use time-of-day travel time databases to characterize normal travel times on roads. This information is used by traffic management centers together with information from sensors in the highway to identify problems and to make alternate route recommendations. In this paper, the travel time database concept is extended to a vehicle-to-vehicle communications network for traffic and safety information, wherein the travel time database is generated and stored by vehicles in the network, and used by the vehicles to identify abnormal traffic conditions. This infrastructure-free approach is attractive due to the potential to eliminate highway sensor and sensor maintenance costs, which are major factors that limit the growth of traffic information beyond major roadways in urban regions. Initial work indicates that database storage requirements in the vehicle should be manageable.

In this paper, we develop a methodology to enable the isolation of the heat release contribution of knocking combustion from flame-propagation combustion. We first address the empirical modeling of individual non-autoigniting combustion history using the Wiebe function, and subsequently apply this methodology to investigate the effect of autoignition on the heat release history of knocking cycles in a spark ignition (SI) engine. We start by re-visiting the Wiebe function, which is widely used to model empirically mass burned histories in SI engines. We propose a method to tune the parameters of the Wiebe function on a cycle-by-cycle basis, i.e., generating a different Wiebe to suitably fit the heat release history of each cycle. Using non-autoigniting cycles, we show that the Wiebe function can reliably simulate the heat release history of an entire cycle, if only data from the first portion of the cycle is used in the tuning process.

An analytical study of spray from an outwardly opening pressure swirl injector has been presented in this paper. A number of model injectors with varying design configurations have been used in this study. The outwardly opening injection process has been modeled using a modified spray breakup model presented in an earlier study. It has been observed that simulation results from the study clearly capture the mechanism by which an outwardly opening conical spray interacts with the downstream flow field. Velocity field near the tip of the injector shows that the conical streams emanating from an outwardly opening injector have the tendency to entrap air into the flow stream which is responsible for finer spray. A deviation from the optimum set of physical parameters showed a high propensity to produce large spray droplets. This study also emphasizes the importance of computational fluid dynamics (CFD) as an engineering tool to understand the complex physical processes.