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Regarding the strongly growing two-wheeler market fuel economy, price and emission legislations are in focus of current development work. Fuel economy as well as emissions can be improved by introduction of engine management systems (EMS). In order to provide the benefits of an EMS for low cost motorcycles, efforts are being made at BOSCH to reduce the costs of a port fuel injection (PFI) system. The present paper describes a method of how to reduce the number of sensors of a PFI system by the use of sophisticated software functions based on high-resolution engine speed evaluation. In order to improve the performance of a system working without a MAP-sensor (manifold air pressure sensor) an air charge feature (ACFn) based on engine speed is introduced. It is shown by an experiment that ACFn allows to detect and adapt changes in manifold air pressure. Cross-influences on ACFn are analyzed by simulations and engine test bench measurements.

Cost reduction of engine management systems (EMS) for two-wheeler applications is the key to utilize their potentials compared to carburetor bikes regarding emissions, fuel economy and system robustness. In order to reduce the costs of a system with port fuel injection (PFI) Bosch is developing an EMS without a manifold air pressure (MAP) sensor. The pressure sensor is usually used to compensate for different influences on the air mass, which cannot be detected via the throttle position sensor (TPS) and mean engine speed. Such influences are different leakage rates of the throttle body and changing ambient conditions like air pressure. Bosch has shown in the past that a virtual sensor relying on model based evaluation of engine speed can be used for a detection of leakage air mass in idling to improve the pre-control of the air-fuel ratio. This provides a functionality which so far was only possible with an intake pressure sensor.

In order to fulfil emission legislation and achieve good drivability of combustion-engine-powered vehicles, information about the air charge and feedback about the engine condition is necessary. In current systems, different sensors are used, e.g. the MAP (manifold air pressure) sensor and a lambda sensor. Aiming at reducing costs, efforts are being made to reduce the number of sensors while still retrieving the necessary information. Various engine speed based functions are state-of-the-art for automotive engines, e.g. for fuel-calibration, misfire-detection etc. Those functions evaluate the engine speed fluctuations during a working cycle induced by combustion. For multiple-cylinder engines, those influences are overlapping, therefore evaluation possibilities are limited. The work presented is based on the effect that at a single-cylinder engine, there is no overlap of combustion influences of various cylinders on the crankshaft.

In order to optimize the performance and emission of engines, advanced control and diagnostic systems require detailed feedback information about the combustion process. In this context, cost-effective solutions are of interest. The contribution describes a method for reconstructing cylinder-individual features of each combustion cycle by processing the instantaneous fluctuations of the engine speed and the in-cylinder pressure of one cylinder. Model-based torque estimation, analyzing both of the signals simultaneously, provides an accurate estimation of the mean indicated pressure. Using this method, a new algorithm for advanced misfire detection is presented. Furthermore, a new pressure model with a feasible number of parameters is proposed. It is combined with the torque estimation in order to reconstruct the unknown pressure traces of the cylinders not equipped with sensors.