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Classical diesel engine combustion with relatively short ignition delay, including papers dealing with low CR and high EGR calibrations are included in this technical paper collection.

This technical paper collection covers transmission and driveline modeling, including topics related to transmission hardware, software, and system integration.

The technical paper collection covers advances in the development and application of models and tools involved in multi-dimensional engine modeling. This includes advances in chemical kinetics, combustion and spray modeling, turbulence, heat transfer, mesh generation, and approaches targeting improved computational efficiency.

This technical paper collection covers DOC, HC Trap, DPF, GPF, LNT, TWC, SCR, SCRF, ammonia oxidation catalysts, hybrid or combined catalysts, urea-water solution spray dynamics, and mixture non-uniformity. Modeling aspects range from fundamental, 3D models of individual components to system level simulation, optimization, variation, degradation, and control.

This technical paper collection advances the knowledge in the state of the art in all types of sheet metal forming. Topics include using simulated, analytical, numerical and experimental tools and sheet metals for the various forming technologies.

This technical paper collection covers papers describing experiments and test data, simulation results focused on applications, fuel/additive effects, combustion control, and mode change. Papers with an emphasis on the modeling aspects of combustion are also included.

Classical HCCI combustion with temperature controlling combustion onset and only a modest effect of fuel injection. Papers describing experiments and test data, simulation results focused on applications, fuel/additive effects, combustion control, and mode change are invited and will be placed in appropriate sub-sessions.

Papers cover exhaust aftertreatment system models, as well as their validation and application. Technologies encompassed include DOC, HC Trap, DPF, GPF, LNT, TWC, SCR, SCRF, ammonia oxidation catalysts, hybrid or combined catalysts, urea-water solution spray dynamics, and mixture non-uniformity. Modeling aspects range from fundamental, 3D models of individual components to system level simulation, optimization, variation, degradation, and control.

This technical paper collection will showcase the creation and application of various tools that will allow for the design and manufacture of parts, equipment, facilities and tests that eliminate the need for physical part prototyping early in a program. The ability to model various aspects of design, test and manufacturing allows for more accurate, cost effective and faster development and product delivery to market.

The papers in this collleciton focus on state of the art simulation technologies for modeling thermal systems and their application in the development and optimization of vehicle thermal management and fuel economy. The papers range from empirical, 1D modeling methods to three dimensional CFD models as well as coupled methods.

The papers in this collleciton focus on state of the art simulation technologies for modeling thermal systems and their application in the development and optimization of vehicle thermal management and fuel economy. The papers range from empirical, 1D modeling methods to three dimensional CFD models as well as coupled methods

This collection of papers focus on state-of-the-art fatigue theory and advanced development in fatigue testing, material behavior under cyclic loading, and fatigue analysis methodology & research in the ground vehicle industry. Studies and discussions on innovative and improved fatigue theory/methods in will be discussed along with and engineering applications of CAE durability analysis.

This collection papers advances the knowledge in product design, manufacturing processes, and engineering analysis using the state-of-the-art computer technology. The scope includes such areas as CFD, manufacturing and assembly simulation, crash-worthiness, computational mechanics, mold flow, ride simulation, ergonomic design, NVH, reverse engineering, etc. Developments in numerical methods applicable to automotive engineering problems are also included.

Classical HCCI combustion with temperature controlling combustion onset and only a modest effect of fuel injection. Papers describing experiments and test data, simulation results focused on applications, fuel/additive effects, combustion control, and mode change are invited are included in this collection.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

Classical HCCI combustion with temperature controlling combustion onset and only a modest effect of fuel injection. Papers describing experiments and test data, simulation results focused on applications, fuel/additive effects, combustion control, and mode change are invited are included in this collection.

Abstract Traditionally driveline ratios are selected based on trial and error method of proto vehicle testing. This consumes lot of time and increases overall vehicle development effort. Over last few decades, simulation-based design approach has been extensively used to alleviate this problem. This paper describes torque converter and final drive ratio (FDR) selection at concept phase for new Automatic Transmission (AT) vehicle development. Most of the critical data required for simulating vehicle performance and fuel economy (FE) targets were not available (e.g. shift map, clutch slip map, pedal map, dynamic torque, coast down, etc.) at an initial stage of the project. Hence, the risk for assuming right inputs and properly selecting FDR/Torque converter was particularly high. Therefore, a validated AVL Cruise simulation model based on an existing AT vehicle was used as a base for new AT vehicle development to mitigate the risk due to non-availability of inputs.

Abstract In today’s competitive automobile market, driver comfort is at utmost importance and the bar is being raised continuously. Gear Shifting is a crucial customer touch point. Any issue or inconvenience caused while shifting gear can result into customer dissatisfaction and will impact the brand image. While there are continual efforts being taken by most of the car manufactures, “Double Bump” in gearshift has remained as a pain area and impact severely on the shift feel. This is more prominent in North-South (N-S) transmissions. In this paper ‘Double Bump’ is a focus area and a mathematical / analytical approach is demonstrated by analyzing ‘impacting parameters’ and establishing their co-relation with double bump. Additionally, the results are also verified with a simulation model.

Abstract In this article performance of the innovative Crank-Lever Electromagnetic Damper (CLEMD) for an off-road vehicle suspension system is analyzed. To determine the characteristic behavior of the CLEMD, the damping force it provides on the suspension system is varied by changing the values of the damping coefficient in the simulations. Various parameters considered in the analyses include power regenerated, voltage, current, comfort, road-holding, etc. The behavior of all the parameters of the CLEMD is observed for an off-road vehicle by carrying out simulations on country roads since the off-road vehicles are subjected to higher road irregularities and hence provide an opportunity to regenerate a higher amount of power. A two-dimensional (2-D) model of a vehicle developed in SimMechanics is interfaced with a Simulink model of CLEMDs for the analyses.

Abstract Obstacle avoidance is an important function in self-driving vehicle control. When the vehicle move from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. There are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. In this paper reinforcement learning is applied to the problem to form effective strategies. There are two major challenges that make self-driving vehicle different from other robotic tasks. Firstly, in order to control the vehicle precisely, the action space must be continuous which can’t be dealt with by traditional Q-learning. Secondly, self-driving vehicle must satisfy various constraints including vehicle dynamics constraints and traffic rules constraints. Three contributions are made in this paper.