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Air pollution levels in an urban environment is a major concern for developed and developing countries alike. Governments around the world are constantly trying to control and reduce air pollution levels through regulations. Low emission zones are being designated in cities worldwide in order to reduce the level of pollutants in big cities. The automotive industry is affected by those regulations and they are becoming more demanding over the years. Present work is aimed at developing a control strategy for a hybrid vehicle in order to optimize the fuel economy and emission levels based on GPS information, driver specific driving characteristics and weather forecast data for a given route. It uses powertrain model of a hybrid vehicle for developing route and driver specific control strategy. The full vehicle model has two sub-models: a route selector and a powertrain optimization model. The route selector selects the optimum route for the vehicle based on energy consumption considering possible routes for reaching the destination. Then the performance is optimized for the selected route using a cost function, which considers route segments which include low emission zone and available data for the headwind during the journey. The results identified the option for choosing strategy for improving both fuel economy and emission levels for a given route.

Route Selection Strategy for Hybrid Vehicles Based on Energy Management and Real Time Drive Cycles