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With the advancement of simulation software development, the efficiency of vehicle and powertrain controls research and development can be significantly improved. Traditionally, during the development of a new control algorithm, dyno or on-road testing is necessary to validate the algorithm. Physical testing is not only costly, but also time consuming. In this study, a virtual platform is developed to reduce the effort of testing. To improve the simulation accuracy, co-simulation of multiple software is suggested as each software specializes in certain area. The Platform includes Matlab Simulink, PTV Vissim, Tass Prescan and AVL Cruise. PTV Vissim is used to provide traffic environment to PreScan. PreScan is used for ego vehicle simulation and visualization. Traffic, signal and road network are synchronized in Vissim and PreScan. Powertrain system is simulated in Cruise. MATALB/Simulink serves as master of this co-simulation, and integrates the different software together.

With the advancement of the autonomous vehicle development, the different possibilities of improving fuel economy have increased significantly by changing the driver or powertrain response under different traffic conditions. Development of new fuel-efficient driving strategies requires extensive experiments and simulations in traffic. In this paper, a fuel efficiency simulator environment with existing simulator software such as Simulink, Vissim, Sumo, and CarSim is developed in order to reduce the overall effort required for developing new fuel-efficient algorithms. The simulation environment is created by combining a mid-sized sedan MATLAB-Simulink powertrain model with a realistic microscopic traffic simulation program. To simulate the traffic realistically, real roads from urban and highway sections are modeled in the simulator with different traffic densities.

Many leading companies in the automotive industry have been putting tremendous amount of efforts into developing new designs and technologies to make their products more energy efficient. It is straightforward to evaluate the fuel economy benefit of an individual technology in specific systems and components. However, when multiple technologies are combined and integrated into a whole vehicle, estimating the impact without building and testing an actual vehicle becomes very complex, because the efficiency gains from individual components do not simply add up. In an early concept phase, a projection of fuel efficiency benefits from new technologies will be extremely useful; but in many cases, the outlook has to rely on engineer’s insight since it is impractical to run tests for all possible technology combinations.