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Time-averaged temperatures at critical locations on the piston of a direct-fuel injected, two-stroke, 388 cm3, research engine were measured using an infrared telemetry device. The piston temperatures were compared to data [7] of a carbureted version of the two-stroke engine, that was operated at comparable conditions. All temperatures were obtained at wide open throttle, and varying engine speeds (2000-4500 rpm, at 500 rpm intervals). The temperatures were measured in a configuration that allowed for axial heat flux to be determined through the piston. The heat flux was compared to carbureted data [8] obtained using measured piston temperatures as boundary conditions for a computer model, and solving for the heat flux. The direct-fuel-injected piston temperatures and heat fluxes were significantly higher than the carbureted piston. On the exhaust side of the piston, the direct-fuel injected piston temperatures ranged from 33-73 °C higher than the conventional carbureted piston.

The need for accurate virtual prototyping prediction is well documented in the literature. For welded body structures one notable shortcoming has been the ability for finite element analysis (FEA) to accurately predict the failure of welded joints due to cyclic loading. A new approach to representing spot-welds for durability evaluation in automotive sheet metal structures is presented here. Excellent correlation with spot-weld failures in actual tests have been observed through this modeling approach. We present a method of representing spot-welds using the finite element method. This method has shown to be able of predicting the behavior of spot-welds prior to the build of any prototypes or testing. Further, for spot-weld failures we present evidence that reveals which radial quadrant of the spot-weld will contain the failure. This method also allows engineers to determine the mechanism of failure. This paper describes in detail the spot-weld modeling method.

As automotive OEMs (Original Equipment Manufacturer) struggle to reach a balance between Design and Performance, environmental legislations continues to demand more rapid gains in vehicle efficiency. As a result, more attention is being given to the contributions of both tire and wheels. Not only tire rolling resistance, but also tire and wheel aerodynamics are being shown to be contributors to overall efficiency. To date, many studies have been done to correlate CFD simulations of rotating wheels both in open and closed wheeled environments to windtunnel results. Whereas this ensures proper predictive capabilities, little focus has been given to thoroughly explaining the physics that govern this complex environment. This study seeks to exhaustively investigate the complex interactions between the ground, body, and a rotating tire/wheel.

An interactive tool for predicting the performance of vehicle designs in the pedestrian leg impact test has been developed. This tool allows users to modify the design of a vehicle front structure through the use of a graphical interface, and then evaluates the performance of the design with a response surface. This performance is displayed in the graphical interface, providing the user with nearly instantaneous feedback to his design changes. An example is shown that demonstrates how the tool can be used to help guide the user towards vehicle designs that are likely to improve performance. As part of the development of this tool, a simplified, parametric finite element model of the front structure of the vehicle was created. This vehicle model included eleven parameters that could be adjusted to change the structural dimensions and structural behavior of the model.

This paper presents an overview of the aerodynamic development of the 2019 Chevrolet Corvette C7 ZR1. Extensive wind tunnel testing and computational fluid dynamics simulations were completed to engineer the ZR1’s aerodynamics to improve lift-to-drag efficiency and track capability over previous Corvette offerings. The ZR1 architecture changes posed many aerodynamic challenges including increased vehicle cooling, strict packaging demands, wider front track width, and aggressive exterior styling. Through motorsports-inspired aerodynamic development, the ZR1 was engineered to overcome these challenges through the creation of new devices such as a raised rear wing and front underwing. The resulting Standard ZR1 achieved a top speed of 212 mph making it the fastest Corvette ever [1]. Optionally, the ZR1 with the ZTK Performance Package provides the highest downforce of any Corvette, generating approximately 950 pounds at the ZTK’s top speed [1].

As one of many pack-level battery simulation approaches developed within the General Motors-led Computer-Aided Engineering of Automotive Batteries (CAEBAT) Phase 1 project, the system approach treats the entire battery pack as a dynamic system which includes multiple engineering disciplines for simulation. It is the most efficient approach of all the CAEBAT battery pack-level approaches in terms of computational time and resources. This paper reports the application of the system approach for a 24-cell liquid-cooled prototype battery pack. It also summarizes the verification of the approach by comparing the simulation results with the measurement data. The results using the system approach are found to have a very good agreement with the measurements.

Internal combustion engines (ICEs) exhaust emissions, particularly nitrogen oxides (NOx), have become a growing environmental and health concern. The biggest challenge for contemporary ICE industry is the development of clean ICEs, and the use of advanced design tools like Computational Fluid Dynamics (CFD) simulation is paramount to achieve this goal. In particular, the development of aftertreatment systems like Selective Catalyst Reduction (SCR) is a key step to reduce NOx emissions, and accurate and efficient CFD models are essential for its design and optimization. In this work, we propose a novel 3D-CFD methodology, which uses a Machine Learning (ML) approach as a surrogate model for the SCR catalyst chemistry, which aims to enhance accuracy of the simulations with a moderate computational cost. The ML approach is trained on a dataset generated from a set of 1D-CFD simulations of a single channel of an SCR catalyst.

Vehicle dynamics simulation with Hardware In the Loop (HIL) has been demonstrated to reduce development and validation time for dynamic control systems. For dynamic control systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC), an accurate vehicle dynamics performance simulation system requires the Electronic Brake Control Module (EBCM) coupled with the vehicles brake system hardware. This kind of HIL simulation-specific software tool can further increase efficiency by means of automation and optimization of the development and validation process. This paper presents a method for HIL vehicle dynamics simulator optimization through Brake Response Time (BRT) correlation. The paper discusses the differences between the physical vehicle and the HIL vehicle dynamics simulator. The differences between the physical and virtual systems are used as factors in the development of a Design Of Experiment (DOE) quantifying HIL simulator performance.

The friction material is arguably at the heart of any brake system, with its properties taking one of the most important roles in defining its performance characteristics. High performance applications, such as race track capable brake systems in high powered vehicles, exert considerable stress on the friction materials, in the form of very high heat flux loads, high clamp and brake torque loads, and high operating temperatures. It is important, for high performance applications, to select capable friction materials, and furthermore, it is important to understand fully what operating conditions the friction material will face in the considered application.

The objective of the paper is to outline a CFD based lumped parameter method that compares the thermal performance of brake rotors, predicts the transient temperatures and brake lining wear in vehicle. A two-pronged approach was developed for this purpose. A rotor stand-alone model was used to predict rotor performance curves. Simultaneously heat transfer coefficients of the brake rotor were computed corresponding to the rotor performance curves and the appropriate heat transfer correlations were established. The second part of this approach involved developing a brake model in a vehicle and solving for the air flow through rotors in different vehicles at various speeds. These rotor flows were cross-referenced with the rotor performance curves, generated earlier for that rotor, to compute the heat transfer coefficients in the vehicle.

The GM Aerodynamics Laboratory (GMAL) was modified in 2001 to reduce the background noise level and provide a semi-anechoic test section for wind noise testing. The walls and ceiling of the test section were lined with acoustic foam and foam-filled turning vanes were installed in the corners. Portions of the wind tunnel circuit were also treated with fiberglass material covered by perforated sheet metal panels. High skin drag due to roughness of the foam surfaces, along with high blockage due to the large turning vanes, increased the wind tunnel circuit losses so that the maximum wind speed in the test section was reduced. The present study calculates the averaged total pressure losses at three locations to evaluate the reductions in skin drag and blockage from proposed modifications to the circuit, which were intended to increase the test section wind speed without compromising noise levels.

Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

The paper provides an overview of a developed methodology and a toolchain for modeling and control of a complex aftertreatment system for passenger cars. The primary objective of this work is to show how the use of this methodology allows to streamline the development process and to reduce the development time thanks to a model based semi-automatic control design methodology combined with piece-wise optimal control. Major improvements in passenger car tailpipe NOx removal need to be achieved to fulfil the upcoming post EURO 6 norms and Real Driving Emissions (RDE) limits. Multi-brick systems employing combinations of multiple Selective Catalytic Reduction (SCR) catalysts with an Ammonia Oxidation Catalysts, known also as Ammonia Clean-Up Catalyst (CUC), are proposed to cover operation over a wide temperature range. However, control of multi-brick systems is complex due to lack of available sensors in the production configurations.

Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

Automotive cruise control systems are used to automatically maintain the speed of a vehicle at a desired speed set-point. It has been shown that fuel economy while in cruise control can be improved using advanced control methods. The objective of this paper is to validate an Adaptive Nonlinear Model Predictive Controller (ANLMPC) implemented in a vehicle equiped with standard production Powertrain Control Module (PCM). Application and analysis of Model Predictive Control utilizing road grade preview information has been reported by many authors, namely for commercial vehicles. The authors reported simulations and application of linear and nonlinear MPC based on models with fixed parameters, which may lead to inaccurate results in the real world driving conditions. The significant noise factors are namely vehicle mass, actual weather conditions, fuel type, etc.

A study on the effect of indenting power-law shaped profiles on the flexible structures for investigating the vibration damping characteristics using computational simulation method is discussed. The simulation results are checked to see the impact of such features on the damping behavior of flexible structures responsible for radiating noise when excited with fluctuating loads. Though the conventional remedies for solving Noise and vibration issues generally involves tuning of structure stiffness or damping treatment this paper gives an insight on the idea of manipulation of elastic waves within the flexible structure itself to minimize the cross-reflections of the mechanical waves. The simulation studies mentioned in this paper not only hovers over the effectiveness of such features but also will be helpful for the engineers to look through a different perspective while solving N&V issues using simulation tools.

The paper examines how the issue of lengthy development times can be mitigated by adopting a multivariable physics based control method for the development and deployment of complex engine control algorithms required for modern diesel engines equipped with Lean NOx Trap aftertreatment technology. The proposed approach facilitates manufacturers to consider lower cost powertrain configurations for selected markets while maintaining higher performance configurations for other markets. The contribution includes on-engine results from joint work between General Motors and Honeywell. The Honeywell OnRAMP Design Suite which applies model predictive control techniques was used for model identification, control design (using model predictive control) and its calibration. With no prior work on the engine this process of calibrating an engine model and achieving transient drive cycle control on the engine required ten days in the test cell and five days of offline work using the OnRAMP software.

In order to reduce the number of head injuries sustained by pedestrian accidents, safety engineers are developing pedestrian friendly hood systems through gauge optimization of the hood inner panel. In this study, the clinch method was employed to assemble a pedestrian friendly hood with a 0.5mm thick inner panel. Static and dynamic analyses were carried out to determine the clinch experiencing the highest loads and to understand the fatigue behavior of a clinched hood during a slam event. The macroscopic failure modes of clinched joints by hood slam were studied by means of a scanning electron microscope. A simple equation was derived to correlate the hexahedron spot weld model as a substitute for clinching in order to obtain an equivalent stiffness for a clinched joint within the linear region of an F-D curve. The F-D curve was obtained by lap shear testing.

Turbocharger maps measured on a gas stand test bench are commonly used to represent turbine and compressor performance. The maps are useful source of information for mean value modeling, engine calibration optimization, virtual sensing and feedback control design. For some tasks, representing the maps by fitted functional forms can be more convenient than using interpolation of the map data directly. The functional representation usually allows for wider extrapolation ranges and more reliable application of numerical optimization methods. In literature most successful functional forms chosen to represent the compressor flow characteristics are based on rational polynomials of dimensionless head and flow parameters. Turbine flow characteristics, on the other hand, are commonly modeled as orifices or orifices with variable cross-section in case of variable geometry turbines (VGT).

The objective of this paper is to develop an analytical approach to compute cooling airflow at any particular fan and vehicle speed condition in a vehicle from a minimum number of CFD (Computational Fluid Dynamic) simulations or test runs using fan performance data. The vehicle system resistance is used with fan performance curves to find the cooling airflows of the vehicle. Fan performance curves at any fan speed are computed using fan laws and the CFD simulations are used in computing the system resistances at a particular vehicle speed. The paper outlines the prediction of system resistances at other vehicle speeds and its use in computing the cooling flows at those speeds. The approach is validated using CFD for different combinations of vehicle and fan speeds.