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Real Driving Emission (RDE) norms have changed the way vehicles are required to be calibrated and developed. This has moved the legislative requirements from predictable lab conditions to more realistic, real world conditions. Current Indian legislation allows certification for Heavy Duty (HD) applications on engine level and therefore decoupled from vehicle and the real world scenarios such as uncertainty and randomness in driver behavior, traffic conditions, road profiles, ambient conditions etc. which are not captured. Upcoming RDE legislation to be implemented in year 2023, has made it necessary to integrate engine with vehicle to consider the impact of various parameters on engine operating points and therefore on tail pipe emissions. This paper focusses upon the methodology developed using RDE cycle generator tool (RCG) for generating on-road parameters which influences the zone of engine operation and resulting emission levels.

This paper analyses the potential of dual clutch transmissions for MD and HD commercial vehicles in India. It compares vehicle performance, i.e. duration of a given transport cycle, and fuel consumption during this transport cycle for a 49 to. long haulage truck under typically given driving conditions in India. Additionally a performance comparison between 6 speed and 8 speed transmissions on long haul trucks in India is shown. The performance of different transmission types (MT, AMT and DCT) as well as 6 respectively 8 speed transmissions for each transmissions type are compared and discussed. The fuel efficiency as well as the cycle time of each individual transmission have been analyzed by powertrain system simulations. Furthermore the design of a modular transmission family concept for commercial vehicles (truck & bus) is presented. It combines both, a manual transmission as well as a powershift capable double clutch transmission within the same transmission family.

Due to more stringent emission standards as well as customer requirements on performance improvement, model-based controls in diesel engines are becoming more and more common and necessary. In fact, as diesel engines becoming increasingly complicated with additional hardware components such as electonic throttle, EGR, VVT, VGT, as well as aftertreatment devices, the dynamics of the systems with more freedom of multiple actuators become much more sophisticated. With such complexity in the diesel engine systems, the traditional simple PI control, single-input single-output type of controls will not be good enough to address the multivariable interactions among subsystems, instead the advanced model-based, multi-input multi-output and coordinated supervisory controls almost become the only effective ways to improve system performance and achieve emission standards.

The eHorizon unit enables the possibility to get information of the road ahead in a defined prediction horizon. This data, like road gradient, curve radius, velocity limitation and road class, can be used by the onboard transmission control unit (TCU) via Controller Area Network (CAN) bus. This obtained predictive road information combined with the actual driving conditions can be used to optimize the shifting strategy by a model predictive control (MPC) algorithm which intends to reduce the fuel consumption. In order to solve the optimum problem inside the MPC with less memory, a pre-optimization based dynamic programming (PODP) approach is proposed. In this paper, the predictive gear selection (PGS) strategy will be compared to a conventional automatic gear shifting strategy in a simulation environment and validated on road by implementing it on a heavy-duty truck with a 16-speed automated manual transmission (AMT).