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We have developed a full virtual engine system prototyping platform with 4-cylinder engine plant model, SH-2A CPU hardware model, and object code level software including OSEK OS. The virtual engine system prototyping platform can run simulation of an engine control system and digital knock detection system including 64-pt FFT computations that provide required high-resolution DSP capability for detection and control. To help the system design, debugging, and evaluation, the virtual system prototyping consists of behavior analyzer which can provide the visualization of useful CPU internal information for control algorithm tuning, RTOS optimization, and CPU architecture development. Thus the co-simulation enables time and cost saving at validation stage as validation can be performed at the design stage before production of actual components.

With rapid increase of vehicles on the road, safety concerns have become increasingly prominent. Since the leading cause of many traffic accidents is known to be by human drivers, developing autonomous vehicles is considered to be an effective approach to solve the problems above. Although trajectory tracking plays one of the most important roles on autonomous driving, handling the coupling between trajectory-tracking control and ESP under certain driving scenarios remains to be challenging. This paper focuses on trajectory-tracking control considering the role of ESP. A vehicle model is developed with two degrees of freedom, including vehicle lateral, and yaw motions. Based on the proposed model, the vehicle trajectory is separated into both longitudinal and lateral motion. The coupling effect of the vehicle and ESP is analyzed in the paper. The lateral trajectory-tracking algorithm is developed based on the preview follower theory.

Twent-two participants of varying ages detected roadside targets in two consecutive dynamic evaluations of a horizontally swiveling headlamp vehicle and a vehicle with the same headlamps that did not swivel. Participants detected targets as they drove unlighted low-speed public roads. Scenarios encountered were intersection turns, and curves with approximate radii of 70-90m, 120-140m, 170-190m, and 215-220m. Results from the first study found improved detection distances from the swiveling headlamps in left curves, but unexpectedly decreased detection distances in larger radius right hand curves. The swiveling algorithm was altered for the second study, and the headlamps used did not have the same beam pattern as in the first study. Results from the second study again found improved detection distances from the swiveling headlamps while in the larger radius right hand curves fixed and swivel were not statistically different.

The main objective of this paper is to simulate the springback using combined kinematic/isotropic hardening model. Material parameters in the hardening model are identified by an inverse method. Three-point bending test is conducted on 6022-T4 aluminum sheet. Punch stroke, punch load, bending strain and bending angle are measured directly during the tests. Bending moments are then computed from these measured data. Bending moments are also calculated based on a constitutive model. Material parameters are identified by minimizing the normalized error between two bending moments. Micro genetic algorithm is used in the optimization procedure. Stress-strain curves is generated with the material parameters found in this way, which can be used with other plastic models. ABAQUS/Standard 5.8, which has the combined isotropic/kinematic hardening model, is used to simulate draw-bend of 6022-T4 series aluminum sheet. Absolute springback angles are predicted very accurately.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

In order to increase the efficiency of automotive turbochargers at low speed without compromising the performance at maximum boost conditions, variable geometry compressor (VGC) systems, based on either variable inlet guide vanes or variable geometry diffusers, have been recently considered as a future design option for automotive turbochargers. This work presents a modeling, analysis and optimization study for a Diesel engine equipped with a variable geometry compressor that help understand the potentials of such technology and develop control algorithms for the VGC systems,. A cycle-averaged engine system model, validated on experimental data, is used to predict the most important variables characterizing the intake and exhaust systems (i.e., mass flow rates, pressures, temperatures) and engine performance (i.e., torque, BMEP, volumetric efficiency), in steady-state and transient conditions.

We have developed a model-based control for the air intake system in a variable valve engine, employing total engine simulation, the response surface method and multi-objective optimization scheme. In our technique, we performed the simulation model tuning and validation, followed by the creation of a dataset for the polynomial regression analysis of the charging efficiency. A D-optimal design, robust least squares method, and likelihood-ratio test were demonstrated to yield a robust and accurate control model. Coupling the total engine simulator with a genetic algorithm, model based calibration for optimal valve timing stored in lookup table was carried out under multiple objectives and restrictions. The reliability of the implementation control model, which considers the effect of gas dynamics in the intake system, was confirmed using a model-in-the-loop simulation.

The purpose of this study is to develop model-based methodologies which employ thermo-fluid dynamic engine simulation and multiple-objective optimization schemes for engine control and calibration, and to validate the reliability of the method using a dynamometer test. In our technique, creating a total engine system model begins by first entirely capturing the characteristics of the components affecting the engine system's behavior, then using experimental data to strictly adjust the tuning parameters in physical models. Engine outputs over the full range of engine operation conditions as determined by design of experiment (DOE) are simulated, followed by fitting the provided dataset using a nonlinear response surface model (RSM) to express the causal relationship among engine operational parameters, environmental factors and engine output. The RSM is applied to an L-jetronic® air-intake system control logic for a turbocharged engine.

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.

A driveline differential gear housing or diff-case is the heaviest component of a driveline that rotates at high velocities. core shift during diff-case casting is a major source of imbalance as casting cores can never be placed at the exact intended location. Core shift in the present case is defined as combination of pure translation along the parting plane and tilting about two orthogonal axes. Given the ranges of variation of these shift parameters, large numbers of random sampling of these variations are generated through Monte Carlo method where normal distribution of each of the core shift parameters is assumed. Static unbalance values of the diff-case from each of the instances of core shift is calculated using Boolean operation in MSC Adams View and a nonlinear data set is created. Next, a statistical model is created based on a neutral network-based fitting method to appropriately represent the set.

In this paper, a newly developed three-dimensional (3D) bird's-eye view map drawing technique for car navigation systems is described. Conventional navigation systems give pseudo-perspective views which can not express ruggedness like hills and valleys. Our newly developed navigation system can display undulation of the land from viewpoints above and behind the current position, so that ups and downs of roads along with the driver's destination can be seen easily. The 3D-road map is not only effective during navigation but also during route planning, because it assists in searching for fine views before travel. In order to achieve the 3D-map view, we developed graphics software libraries, which work on a 32-bit RISC processor and on a low-cost graphics accelerator LSI with texture mapping capability. The graphics software libraries are constructed with three stages, the perspective projection stage, visible-surface determination stage, and rendering stage.

The problem of high fatal accident rates due to drunk driving persists, and must be reduced. This paper reports on a prototype system mounted on a car mock-up and a prototype portable system that enables the checking of the drivers’ sobriety using a breath-alcohol sensor. The sensor unit consists of a water-vapor-sensor and three semiconductor gas sensors for ethanol, acetaldehyde, and hydrogen. One of the systems’ features is that they can detect water vapor from human-exhaled breath to prevent false detection with fake gases. Each gas concentration was calculated by applying an algorithm based on a differential evolution method. To quickly detect the water vapor in exhaled breath, we applied an AC voltage between the two electrodes of the breath-water-vapor sensor and used our alcohol-detection algorithm. The ethanol level was automatically calculated from the three gas sensors as soon as the water vapor was detected.

Electro-mechanical actuators are widely used in different forms in the automotive industry these days and are very effective in translating rotary motion of the motor to a linear motion with precision as per the requirement. With onset of electric drivelines and other complex driveline configurations, there is an increase in actuator applications. In this study, high fidelity analytical model was developed for a ball ramp clutch actuation system as per the proposed mechanical design and the software controls. The controls architecture is built in SIMULINK environment to drive the plant model of the BLDC motor. Whereas, the entire mechanical system which includes the gear train, ball ramp mechanism, clutch pack stiffness, etc. is modelled in ADAMS tool. The Ball Ramp consists of metal balls positioned in between opposing paired arc-shaped ramp grooves and guided by a cage to keep them equally separated in the same plane.

In recent years, integrated vehicle control systems have been developed to improve fuel economy and safety. As a result, engine control is shifting to torque-based systems for throttle / fuel / ignition control, to realize an engine torque demand from the system. This paper describes torque-based engine control technologies for SI (Spark Ignition) engine to improve torque control accuracy using a feedback control algorithm and an airflow sensor.