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Weight reduction is very important in automotive design because of stringent demand on fuel economy. Structural optimization of dynamic systems using finite element (FE) analysis plays an important role in reducing weight while simultaneously delivering a product that meets all functional requirements for durability, crash and NVH. With advancing computer technology, the demand for solving large FE models has grown. Optimization is however costly due to repeated full-order analyses. Reanalysis methods can be used in structural vibrations to reduce the analysis cost from repeated eigenvalue analyses for both deterministic and probabilistic problems. Several reanalysis techniques have been introduced over the years including Parametric Reduced Order Modeling (PROM), Combined Approximations (CA) and the Epsilon algorithm, among others.

To improve fuel economy, there is a trend in automotive industry to use light weight, high strength materials. Automotive body structures are composed of several panels which must be downsized to reduce weight. Because this affects NVH (Noise, Vibration and Harshness) performance, engineers are challenged to recover the lost panel stiffness from down-gaging in order to improve the structure borne noise transmitted through the lightweight panels in the frequency range of 100-300 Hz where most of the booming and low medium frequency noise occurs. The loss in performance can be recovered by optimized panel geometry using beading or damping treatment. Topography optimization is a special class of shape optimization for changing sheet metal shapes by introducing beads. A large number of design variables can be handled and the process is easy to setup in commercial codes. However, optimization methods are computationally intensive because of repeated full-order analyses.

The cathode gas diffusion layer (GDL) is an important component of polymer electrolyte membrane (PEM) fuel cell. Its design parameters, including thickness, porosity and permeability, significantly affect the reactant transport and water management, thus impacting the fuel cell performance. This paper presents an optimization study of the GDL design parameters with the objective of maximizing the current density under a given voltage. A two-dimensional single-phase PEM fuel cell model is used. A multivariable optimization problem is formed to maximize the current density at the cathode under a given electrode voltage with respect to the GDL parameters. In order to reduce the computational effort and find the global optimum among the potential multiple optima, a global metamodel of the actual CFD-based fuel cell simulation, is adaptively generated using radial basis function approximations.

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.

With increasing demand for cost-effective fuel cells, it is essential to investigate alternative materials for components of the fuel cells. The objective of this paper is to implement elastomeric materials (silicon rubber) for the use of bipolar plates in a polymer electrolyte membrane fuel cell. Two different types of conductive fillers, a graphite fiber and flake, were added at different concentrations to a two-component silicone rubber slurry. Electrical, thermal and mechanical properties of the composite material were investigated. Comparable electrical and thermal conductivities were achieved to that of commercially available plates. The silicone rubber based composite material maintained elastomeric properties for improved sealing of cell fluid reactants and products.

Polymer Electrolyte Membrane (PEM) fuel cells have grown in research and development for many applications due to their high efficiency and humble operating condition requirements. Water management in the cathode region of the PEM fuel cell is an essential and sensitive phenomenon for cold environments and fuel cell’s performance. This paper investigates the behavior of water production by constructing a transparent-cathode PEM fuel cell. The effects of pressure, relative humidity, and cathode stoichiometric ratio on the production of water as a function of time were studied. Each test set is compared to a reference state. The images of water liquid accumulation inside the cathode bipolar plate channels are shown with the corresponding polarization curves.

The advantages of having higher stiffness to weight ratio and strength to weigh ratio that composite materials have resulted in an increased interest in them. In automotive engineering, the weight savings has positive impacts on other attributes like fuel economy and possible noise, vibration and harshness (NVH). The driveline of an automotive system can be a target for possible use of composite materials. The design of the driveshaft of an automotive system is primarily driven by its natural frequency. This paper presents an exact solution for the vibration of a composite driveshaft with intermediate joints. The joint is modeled as a frictionless internal hinge. The Euler-Bernoulli beam theory is used. Lumped masses are placed on each side of the joint to represent the joint mass. Equations of motion are developed using the appropriate boundary conditions and then solved exactly.

This paper proposes an approach for optimal design of multilevel systems under uncertainty. The approach utilizes the stochastic extension of the analytical target cascading formulation. The reliability of satisfying the probabilistic constraints is computed by means of the most probable point method using the hybrid mean value algorithm. A linearization technique is employed for estimating the propagation of uncertainties throughout the problem hierarchy. The proposed methodology is applied to a piston-ring/cylinder-liner engine subassembly design problem. Specifically, we assess the impact of variations in manufacturing-related properties such as surface roughness on engine attributes such as brake-specific fuel consumption. Results are compared to the ones obtained using Monte Carlo simulation.

Developments in modern spark ignition (SI) engines such as intake boosting, direct-injection, and engine downsizing techniques have demonstrated improved performance and thermal efficiency, however, these strategies induce significant deviation in end-gas pressure/temperature histories from those of the traditional Research and Motor Octane Number (RON and MON) standards. Attempting to extrapolate the anti-knock performance of fuels tested under the traditional RON/MON conditions to boosted operation has yielded mixed results in both SI and advanced compression ignition (ACI) engines. This consideration motivates the present work with seeks to establish a pathway towards the development of the test conditions of a boosted octane number, which would better correlate to fuel performance at high intake pressure conditions.

A vehicle drivetrain is designed to meet specific vehicle performance criteria which usually involve trade-offs among conflicting performance measures. This paper describes a methodology to optimize the drivetrain design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A complete vehicle dynamic model is developed using the bond graph method. The model includes the vehicle, engine, transmission, torque converter, driveline, and transmission controller. An equivalent MATLAB Simulink model is also developed in order to carry out the nonlinear dynamic analysis efficiently. A deterministic optimization is first performed to determine the optimum design in terms of fuel economy, without considering variations or uncertainties. Subsequently, a Reliability-Based Design Optimization is carried out to find the optimum design in the presence of uncertainty.

Given increasingly stringent emission targets, engine efficiency has become of foremost importance. While increasing engine compression ratio can lead to efficiency gains, it also leads to higher in-cylinder pressure and temperatures, thus increasing the risk of knock. One potential solution is the use of a Variable Compression Ratio system, which is capable of exploiting the advantages coming from high compression ratio while limiting its drawbacks by operating at low engine loads with a high compression ratio, and at high loads with a low compression ratio, where knock could pose a significant threat. This paper describes the design of a model for the evaluation of fuel consumption for an engine equipped with a VCR system over representative drive cycles. The model takes as inputs; a switching time for the VCR system, the vehicle characteristics, engine performance maps corresponding to two different compression ratios, and a drive cycle.

Variable Compression Ratio systems are an increasingly attractive solution for car manufacturers in order to reduce vehicle fuel consumption. By having the capability to operate with a range of compression ratios, engine efficiency can be significantly increased by operating with a high compression ratio at low loads, where the engine is normally not knock-limited, and with a low compression ratio at high load, where the engine is more prone to knock. In this way, engine efficiency can be maximized without sacrificing performance. This study aims to analyze how the effectiveness of a VCR system is affected by various powertrain and vehicle parameters. By using a Matlab model of a VCR system developed in Part 1 of this work, the influence of the vehicle characteristics, the drive cycle, and of the number of stages used in the VCR system was studied.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

This paper presents nonlinear system identification of a variable oil pump for model-based controls and diagnostics of advanced internal combustion engines. The variable oil pump offers great benefits over the conventional fixed displacement oil pump in terms of fuel efficiency and functional optimality. However, to fully benefit from the variable oil pump, an accurate mathematical model that describes its dynamic behavior is foundational to develop an accurate and robust oil pressure control and diagnostic. Toward this end, Hammerstein and Wiener models that consist of a nonlinear static block followed by a linear dynamic block and a linear dynamic block followed by a nonlinear static block, respectively are developed. Under different operating conditions (oil temperature and engine speed), the oil pressure (output) is measured with the multilevel duty cycle (input) of the flow control valve.

Expanding upon the authors’ previous work which utilized a GT-Power model of the Cooperative Fuels Research (CFR) engine under Research Octane Number (RON) conditions, this work defines the boundary conditions of the CFR engine under Motored Octane Number (MON) test conditions. The GT-Power model was validated against experimental CFR engine data for primary reference fuel (PRF) blends between 60 and 100 under standard MON conditions, defining the full range of interest of MON for gasoline-type fuels. The CFR engine model utilizes a predictive turbulent flame propagation sub-model, and a chemical kinetic solver for the end-gas chemistry. The validation was performed simultaneously for thermodynamic and chemical kinetic parameters to match in-cylinder pressure conditions, burn rate, and knock point prediction with experimental data, requiring only minor modifications to the flame propagation model from previous model iterations.

Creating a fuel map for simulation of an engine with Variable Valve Actuation (VVA) can be computationally demanding. Design of Experiments (DOE) and metamodeling is one way to address this issue. In this paper, we introduce a sequential process to generate an engine fuel map using Kriging metamodels which account for different engine characteristics such as load and fuel consumption at different operating conditions. The generated map predicts engine output parameters such as fuel rate and load. We first create metamodels to accurately predict the Brake Mean Effective Pressure (BMEP), fuel rate, Residual Gas Fraction (RGF) and CA50 (Crank Angle for 50% Heat Release after top dead center). The last two quantities are used to ensure acceptable combustion. The metamodels are created sequentially to ensure acceptable accuracy is achieved with a small number of simulations.

Engine experiments were conducted on a heavy-duty single-cylinder engine to explore the effects of charge preparation, fuel stratification, and premixed fuel chemistry on the performance and emissions of Reactivity Controlled Compression Ignition (RCCI) combustion. The experiments were conducted at a fixed total fuel energy and engine speed, and charge preparation was varied by adjusting the global equivalence ratio between 0.28 and 0.35 at intake temperatures of 40°C and 60°C. With a premixed injection of isooctane (PRF100), and a single direct-injection of n-heptane (PRF0), fuel stratification was varied with start of injection (SOI) timing. Combustion phasing advanced as SOI was retarded between -140° and -35°, then retarded as injection timing was further retarded, indicating a potential shift in combustion regime. Peak gross efficiency was achieved between -60° and -45° SOI, and NOx emissions increased as SOI was retarded beyond -40°, peaking around -25° SOI.