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Fuel consumption has been a core consideration since the beginning of the transportation era. These are reasons related to our environment, and to economics. In the competitive truck industry fuel consumption is an important sales argument, since customers on an average drive their trucks for distances of 150 000 km per year, which means that fuel becomes a large part of the lifetime cost for a vehicle. Existing braking system design in commercial vehicles are basically air assisted, which utilizes the compressed air from reservoir, which is being replenished based on requirement by a positive displacement compressor, generally driven directly by vehicle power pack. In this paper, an effort has been made to partially use the energy stored in the springs (induced due to road undulations) for compressed air generation through a single acting positive displacement pump.

Fuel consumption for heavy trucks depends on many factors like roads, weather, and driver behavior that are hard for a manufacturer to influence. However, one design possibility is the power-train configuration. Here a new simulation program for heavy trucks is created and the configuration of the power-train that gives the lowest fuel consumption for each transport task is selected based on the simulation results. In this work, the operational conditions have been considered i.e. load, pavement, transmission efficiency and the building characteristics of the engine map, transmission, frontal area, tire. In this paper, we present a simulation software that enables a vehicle manufacturer or a customer to choose the right driveline for the customized application, depending on the acceleration and the fuel economy needs.

Fuel consumption for heavy trucks depends on many factors like roads, weather, and driver behaviour that are hard for a manufacturer to influence. However, one design possibility is the power-train configuration. In this paper, driveline of a heavy-duty truck is optimised using the six-sigma methodology. The focus of the task is selection of a power train configuration that gives the lowest fuel consumption for each transportation task. To reduce fuel consumption, it is important to choose a powertrain combination (gearbox, rear axle, tire dimension) that allows efficient use of the engine. Such an optimization of powertrain configuration is a complex task, but current simulation techniques provide means to reduce costly testing by replacing it partly with analysis. The DMAIC (Define, Measure, Analyze, Improve & Control) steps are followed to generate alternate solutions of the descriptive problem.