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Due to increasing amount of modules and customized options in commercial vehicles, it becomes more and more difficult to verify the circuit design. In this paper, a wire segment error locating algorithm is proposed to automate the exact wire segment error locating process. When a wrong connection is found by existing tool, guided by the exact description of wire segment error, this algorithm can locate exact wire segment error in the connection by searching for the one that has at least one neighboring segment from a correct connection.

A spark-ignition engine commonly induces tumble flow because it generates high turbulence, which is a crucial factor in determining the flame propagation speed. Since tumble affects not only the flame propagation speed but also the various in-cylinder phenomena, it predominantly determines the performance of the engine. In that sense, many studies have been conducted to investigate tumble. Although various studies have revealed the characteristics of tumble numerically and experimentally, there has been no research to identify the physical mechanisms of these characteristics. Although some studies specified the mechanisms from an angular momentum perspective, the theory was insufficient to explain the entire phenomena of tumble. Hence, this study attempts to comprehend the fundamental causes of tumble phenomena such as ‘spinning up’ and ‘vortex breakdown’ from the perspective of kinetic energy.

This paper introduces a systematic wiring guideline which includes coupling noise calculation, wire layout design, and wire type selection methodologies. The coupling theory between wires has been introduced long time ago but it was not successfully applied to real automotive wiring design due to the complexity in the theory such as large number of parameters and many different conditions in automotive wiring environment. In this paper, the complexity is reduced by separating physical parameters and electrical parameters and identifying controllable parameters and given parameters. This paper first introduces parameters which are used in the coupling equations and automotive wiring design, then the coupling noise calculation method which uses the coupling equations is introduced. The systematic automotive wiring guideline which prevents noise problem in various design stage such as system filter design, wire layout design, wire type selection is introduced.

This paper presents a stability monitoring algorithm with a combined slip tire model for maximized cornering speed of high-speed autonomous driving. It is crucial to utilize the maximum tire force with maintaining a grip driving condition in cornering situations. The model-free cruise controller has been designed to track the desired acceleration. The lateral motion has been regulated by the sliding mode controller formulated with the center of percussion. The controllers are suitable for minimizing the behavior errors. However, the high-level algorithm is necessary to check whether the intended motion is inside of the limit boundaries. In extreme diving conditions, the maximum tire force is limited by physical constraints. A combined slip tire model has been applied to monitor vehicle stability. In previous studies, vehicle stability was evaluated only by vehicle acceleration.

This paper describes a driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consists of four parts; speed controller for tracking of the desired speeds, yaw rate controller which computes a yaw moment input to track desired yaw rates, longitudinal tire force distribution which determines an optimal desired longitudinal tire force and wheel torque controller which determines a wheel torque command at each wheel to keep slip ratio at each wheel below a limit value as well as track the desired tire force. Longitudinal and vertical tire force estimators are designed for optimal tire force distribution and wheel slip control. The dynamic model of RVAS for simulation study is validated using vehicle test data.

During icing wind tunnel experiments, the calibration process of the spray nozzle and aerothermal systems introduces experimental uncertainty that can potentially compromise the reliability of the test results. Therefore, performing sensitivity analysis (SA) or uncertainty quantification (UQ) studies is not only essential to determine the influence of uncertainties on the ice shape and aerodynamic performance but also crucial to identify the most significant icing parameter uncertainty. However, given the wide range of icing envelopes, it is not practical to conduct SA and UQ by experimental method because a lot of evaluations are required for SA and UQ study. In this study, we addressed these challenges by using a deep learning-based reduced-order modeling technique.

This paper proposes a rear-wheel steering control method that can modify and improve the vehicle lateral response without tire model and parameter. The proposed control algorithm is a combination of steady-state and transient control. The steady state control input is designed to modify steady-state yaw rate response of the vehicle, i.e. understeer gradient of the vehicle. The transient control input is a feedback control to improve the transient response when the vehicle lateral behavior builds up. The control algorithm has been investigated via computer simulations. Compared to classical control methods, the proposed algorithm shows good vehicle lateral response such as small overshoot and fast response. Specifically, the proposed algorithm can alleviate stair-shaped response of the lateral acceleration.

The flame propagation characteristic is one of the greatest factor that determines the performance of spark ignition (SI) engines. The in-cylinder flow dynamics is very significant in terms of flame propagation because of its direct influence on the flame shape, turbulent flame speed, and the ignition quality. A number of different techniques are available to optimize the in-cylinder flow and maximize the utilization of turbulence for faster combustion, and tumble enhancement by intake port geometry is one of them. It requires excessive computational expenses to evaluate multiple designs under wide range of operating conditions by 3D-CFD, therefore, a low-dimensional model would be more competitive in such design optimization process. This work suggests a new modification approach for typical 0D turbulence model to take account for the tumble generation during the intake process as well as the turbulence characteristics associated with it.

As emissions regulations become stricter, a variety of advanced combustion concepts that can reduce emissions with a higher thermal efficiency have been suggested. Dual-fuel combustion is one of the alternatives that has both premixed and non-premixed combustion characteristics. Knowing the effects of the mixture formation in dual-fuel combustion is important because it determines the ignition location and the following combustion phase. Hence, a thorough investigation on the related factors, such as the engine hardware or fuel spray, is required. Meanwhile, Computational Fluid Dynamics (CFD) is a good technique to visualize the in-cylinder phenomena and enables quantitative investigations into the detailed combustion characteristics. In this paper, a 3-dimensional CFD simulation was used to investigate the effects of the mixture formation in dual-fuel combustion. The combustion model consists of two parts.

Validation of a vehicle simulation model of the Chevrolet Volt 2016 was conducted. The Chevrolet Volt 2016 is equipped with the new “Voltec” extended-range propulsion system introduced into the market in 2016. The second generation Volt powertrain system operates in five modes, including two electric vehicle modes and three extended-range modes. Model development and validation were conducted using the test data performed on the chassis dynamometer set in a thermal chamber of Argonne National Laboratory’s Advanced Powertrain Research Facility. First, the components of the vehicle, such as the engine, motor, battery, wheels, and chassis, were modeled, including thermal aspects based on the test data. For example, engine efficiency changes dependent on the coolant temperature, or chassis heating or air-conditioning operations according to the ambient and cabin temperature, were applied.

Large-eddy simulation (LES) applications for internal combustion engine (ICE) flows are constantly growing due to the increase of computing resources and the availability of suitable CFD codes, methods and practices. The LES superior capability for modeling spatial and temporal evolution of turbulent flow structures with reference to RANS makes it a promising tool for describing, and possibly motivating, ICE cycle-to-cycle variability (CCV) and cycle-resolved events such as knock and misfire. Despite the growing interest towards LES in the academic community, applications to ICE flows are still limited. One of the reasons for such discrepancy is the uncertainty in the estimation of the LES computational cost. This in turn is mainly dependent on grid density, the CFD domain extent, the time step size and the overall number of cycles to be run. Grid density is directly linked to the possibility of reducing modeling assumptions for sub-grid scales.

This paper presents an Interacting Multiple Model (IMM) based side slip angle estimation method to estimate side slip angle under various road conditions for vehicle stability control. Knowledge of the side slip angle is essential enhancing vehicle handling and stability. For the estimation of the side slip angles in previous researches, prior knowledge of tire parameters and road conditions have been employed, and sometimes additional sensors have been needed. These prior knowledge and additional sensors, however, necessitates many efforts and make an application of the estimation algorithm difficult. In this paper, side slip angle has been estimated using on-board vehicle sensors such as yaw rate and lateral acceleration sensors. The proposed estimation algorithm integrates the estimates from multiple Kalman filters based on the multiple models with different parameter set.

A module based IPS (Intelligent Power Switch) evaluation system is proposed in this paper. As the IPS is gradually replacing the conventional relay and fuses, the stability and reliability of power system depends more on these IPS. The proposed IPS evaluation system outperforms the conventional manual evaluation in terms of speed and efficiency. This paper will introduce the structure of hardware and software of the IPS evaluation system. The system is placed between the module and cable connector to evaluate the module in an operating car without changing the cables. The control and signal processing is carried out by personal computer which is connected to the evaluation system by USB (Universal Serial Bus). The load resistance can be switch from actual load to arbitrary value using relay circuitry and DC electric load controlled by GPIB (General Purpose Interface Bus). CAN (Controller Area Network) circuits were added to control the IPS mounted inside the module.

This paper describes the ground system model and algorithm for a ground level simulation tool. First, the modeling of an automotive ground system will be discussed and the algorithm for a simulation tool will be explained. We divided the model into a ground tree and a ground body. The ground tree model consists of resistance formed by the wires that connect the load to ground point with various structures and the ground body model consists of resistance between ground points in the car body. The wires with large current, such as engine ground cable, was modeled in detail by dividing the resistance into wire, bolt, and clamping resistance, in order to simulate the effect of increased contact resistance after durability test. The algorithm of the ground level simulation tool was designed to adjust the currents of the alternator, battery, and ground points in order to evaluate the various driving and load conditions.

This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely.

Two-mode hybrid architectures with three planetary gear sets and four clutches will bring both flexibility and complexity to energy management of powertrains. In order to take full advantage of the increased degrees of freedom, highly delicate operation strategies are needed. We develop transmission efficiency models for power-split modes, and present a mode shift strategy assuming no battery power. When battery load leveling is additionally considered, the respective optimal operation set for each mode can be obtained and compared to yield a mode shift algorithm for general hybrid operation situations. The investigation of the strategies shows how frequently each mode is used, and verifies the effectiveness of fixed gear operations. We check the validity of the strategies by applying the algorithm to dynamic optimization and by predicting how it works during an actual driving simulation.

Characteristics of syngas combustion at various reforming ratios were studied numerically. The syngas was formed by the partial oxidation of methane to mainly hydrogen and carbon monoxide and cooled to ambient temperature. Stiochiometric and lean premixed flames of the mixtures of methane and the syngas were compared at the atmospheric temperature and pressure conditions. The adiabatic flame temperature decreased with the reforming ratio. The laminar burning velocity, however, increased with the reforming ratio. For stretched flames in a counterflow, the high temperature region was broadened with the reforming ratio. The maximum flame temperature decreased with the reforming ratio for the stoichiometric case, but increased for the lean case except for the region of very low stretch rate. The extinction stretch rate increased with the reforming ratio, implying that the syngas assisted flame is more resistance to turbulence level.

Exterior shape of automobile can be represented by shape function through this study so that aerodynamic shape parameters can be easily controlled and changed. Also ordinary geometric information can be extracted easily from shape function model by simple calculations. It is possible to predict the aerodynamic performance of functional virtual car models which are transformed continually by developing automated program in initial design stage that includes all of above process. Innovative vehicle design process with exterior design guide will be proposed for stylist, engineer and packaging department in order to achieve low aerodynamic drag and high fuel efficiency targets.

This paper presents a Unified Chassis Control (UCC) strategy to improve vehicle stability and maneuverability by integrating Electronic Stability Control (ESC) and Active Front Steering (AFS). The UCC architecture consists of two parts: an estimator and a controller. The estimator is designed to estimate longitudinal and lateral tire forces and the controller is designed in two stages, namely, an upper level controller and a lower level controller. The upper level controller, provides the desired yaw moment for vehicle lateral stability by adopting a sliding control method. The lower level controller, provides the integration method of the AFS and ESC strategies for the desired yaw moment and is designed by optimal tire force coordination.

As the number of user selectable electrical modules increases for passenger car, the number of cars with different combinations of option can easily exceed 100,000 cars. It results to a situation where we can not manually verify all the logical connection by making wiring combinations for each car. In this paper, we propose an algorithm that can reduce verification time for all possible wiring with available option combinations. The algorithm separates the whole wiring circuits into independent circuits and verifies the logical connections for each independent circuit with all possible options. The algorithm is time effective so the required time to verify the connections increases logarithmically as the number of possible car increases. The algorithm was implemented as software verification tool and its effectiveness was proved to be feasible.