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The integration of a Dual Mass Flywheel (DMF) in the conventional vehicle driveline leads to various benefits, and hence today it has established its position in many passenger cars and light trucks. Transmission and driveline oscillations are reduced by mechanically decoupling the transmission from the periodic combustion events that excite the engine crankshaft, improving driving comfort and reducing transmission stresses. For systems with conventional single mass flywheel (SMF) reliable engine control systems have already been developed. However, the complexity of the driveline increases with the integration of a DMF. Hence, in the future conventional engine control systems may require adaptation, modification or even replacement, in order to guarantee the optimal control of engines equipped with advanced DMF systems.

Today, in many passenger cars and light trucks, the conventional driveline is extended by a dual mass flywheel (DMF). The DMF reduces driveline oscillations by mechanically decoupling the crankshaft and the transmission. Existing engine control systems are general designed for use with conventional single mass flywheel (SMF) systems. In the future, to facilitate the optimal control of engines equipped with advanced DMF systems, these conventional control systems may require adaptation, modification or even replacement. In the past, misfire detection has been done by expensive dedicated sensors; seismic, ion current measurement at the spark plugs or even by measuring in-cylinder pressures directly. Typically misfire detection is performed using signals derived from the crankshaft position sensor, which works well for engines with a limited number of cylinders and which are connected to relatively simply drivelines.

One goal of modern power train control systems in heavy trucks is to damp driveline oscillations using appropriate controllers. Modern control algorithms like state-space controllers are based on a state-space model, which should accurately characterize the real process behavior. Otherwise, optimal control can not be guaranteed. These state-space models include a huge number of parameters, which have to be identified by an identification process. However, existing driveline models contain two serious problems: an increasing offset over time between measured and simulated data and an inadequate detection of the longitudinal dynamics of the truck. Therefore, this article deals with two goals: to optimize the offline identification process for the special use in driveline systems and to establish an online adaptation of the model parameters to guarantee an optimal model fit.

This paper treats the complete robust H∞ controllers design. The whole synthesis is exemplified by the idle speed control problem at passenger cars and light trucks. Subsequently the robustness of the designed controller is tested and compared to conventional P and PI controllers. The main steps of controller synthesis are described detailed in this work. First, a closed loop structure has to be chosen. For this purpose, basic principles will be introduced. After this, the weighting matrices for the cost functions have to be defined. Finally, the choice of the calculation algorithm is important. In this approach, the idle speed control is done with the Mixed-Sensitivity design and a derivation of the Doyle-Glover (DGKF) algorithm. The choice for the weighting matrices is depicted clearly in the frequency domain. Finally, a comparison between conventional P(I)- controllers and the introduced H∞ - method is demonstrated and discussed.

Today, in many passenger cars and light trucks, the conventional driveline is extended by a dual mass flywheel (DMF). The DMF reduces driveline oscillations by mechanically decoupling the crankshaft and the transmission. Existing engine control systems are designed for conventional single mass flywheel (SMF) systems. In the future, to facilitate the optimal control of engines equipped with advanced DMF systems, such conventional control systems may require adaptation, modification or even replacement. The design and testing of appropriate new control systems has required the development of various types of engine models. In this paper, various engine modeling techniques are introduced and compared in respect to their capabilities for both driveline simulation and control system development.

Over more than 20 years 50 million LuK dual mass flywheels (DMF) have been produced for use in passenger cars and light trucks. A typical DMF consists of two flywheels connected by long travel arc-springs. It is located between the combustion engine and the clutch or automatic transmission. The DMF reduces driveline oscillations by mechanically decoupling the transmission from the periodic combustion events that excite the engine crankshaft. Existing engine control systems are generally designed for conventional single mass flywheel (SMF) systems. In the future, to facilitate the best possible control of engines equipped with DMF systems, these conventional control systems may require modification or even replacement. With the integration of the highly non-linear DMF, the complexity, and thus the order of the powertrain system increase.