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The need for a rigorous systems engineering approach to automotive powertrains has been addressed in this work from the perspective of the diesel engine. A high-fidelity engine simulation has been integrated with a total vehicle model for the purpose of reverse engineering the optimal powerplant for a given vehicle mission. Engine parameters have been coordinated between the simulations to develop a framework for total vehicle design. The design strategies discussed in this paper allow engine researchers to set targets for individual system components and to analyze the tradeoffs associated with different vehicle mission objectives. A detailed case study employing these techniques is presented for a conventional vehicle where the most fuel-efficient engine is found that simultaneously conforms to the desired performance criteria.

This paper investigates the effects of manufacturing variations in fuel injectors on the engine performance with emphasis on emissions. The variations are taken into consideration within a Reliability-Based Design Optimization (RBDO) framework. A reduced version of Multi-Zone Diesel engine Simulation (MZDS), MZDS-lite, is used to enable the optimization study. The numerical noise of MZDS-lite prohibits the use of gradient-based optimization methods. Therefore, surrogate models are developed to filter out the noise and to reduce computational cost. Three multi-objective optimization problems are formulated, solved and compared: deterministic optimization using MZDS-lite, deterministic optimization using surrogate models and RBDO using surrogate models. The obtained results confirm that manufacturing variation effects must be taken into account in the early product development stages.

The target cascading methodology is applied to the conceptual design of an advanced heavy tactical truck. Two levels are defined: an integrated truck model is represented at the top (vehicle) level and four independent suspension arms are represented at the lower (system) level. Necessary analysis models are developed, and design problems are formulated and solved iteratively at both levels. Hence, vehicle design variables and system specifications are determined in a consistent manner. Two different target sets and two different propulsion systems are considered. Trade-offs between conflicting targets are identified. It is demonstrated that target cascading can be useful in avoiding costly design iterations late in the product development process.

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. Aerodynamic drag can also be reduced by close-gap platooning using information from vehicle-to-vehicle communications. In order to achieve these goals, the designers of control strategies need to simulate a wide range of driving situations in which vehicles interact with other vehicles and the infrastructure in a closed-loop fashion. RoadRunner is a new model-based system engineering platform based on Autonomie software, which can collectively provide the necessary tools to predict energy consumption for various driving decisions and scenarios such as car-following, free-flow, or eco-approach driving, and thereby can help in developing control algorithms.

Many of today's advanced simulation tools are suitable for modeling specific systems, but they provide rather limited support for automated model building and management. The diverse tools available for modeling different components of a vehicle make it all the more challenging to comprehend their integration and interactions and analyze the complete system. In addition, the complexities and sizes of the models require a better use of computing resources, such as multicore or remote processing, to greatly reduce the simulation time. In this paper we describe how modern software techniques can support modeling and design activities, with the objective to create system models quickly by assembling them in a “plug-and-play” architecture. System models can be integrated, co-simulated, and reused regardless of the environment in which they are developed, and their simulation results can be consolidated for analysis into a single tool.