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Simulations used to estimate carbon dioxide (CO2) emissions and fuel consumption of medium- and heavy-duty vehicles over prescribed drive cycles often employ engine fuel maps consisting of engine measurements at numerous steady-state operating conditions. However, simulating the engine in this way has limitations as engine controls become more complex, particularly when attempting to use steady-state measurements to represent transient operation. This paper explores an alternative approach to vehicle simulation that uses a “cycle average” engine map rather than a steady state engine fuel map. The map contains engine CO2 values measured on an engine dynamometer on cycles derived from vehicle drive cycles for a range of generic vehicles. A similar cycle average mapping approach is developed for a powertrain (engine and transmission) in order to show the specific CO2 improvements due to powertrain optimization that would not be recognized in other approaches.

Powertrain Control development has gone through many changes in terms of process, tools and practice at all OEM's across the geography. This is mainly driven by increased number of powertrain components for control, shorter development schedules, cost control, and the need to realize the potential of electronic control to increase the performance, efficiency, safety and comfort. With the significant advancement in Powertrain Controls and additions of electronic functions, it has become imperative to automate the controller development process in the V-cycle to reduce the time and make the process more efficient while detecting any logic failures upfront at the early stage of the development cycle. Traditional practices and tools of defining the controls cannot meet new requirements. Model Based Design (MBD) approach is a promising solution to meet the critical needs of powertrain control engineering to define the control logic and validate.