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In the Indian two-wheeler market, legislation and customers demand for a reduction of emissions and an increase of fuel efficiency. For two-wheelers with engine management systems, a cost-efficient approach for this trend exploits that the periodical fluctuation of the engine speed of single cylinder engines contains useful information about its operating conditions. The present article focuses on the quality of the estimation of combustion phasing and air-fuel ratio of a 125cc single cylinder motorcycle engine, obtained from the evaluation of these fluctuations. The robustness of an oxygen sensor-less port fuel injection system can be increased by using the estimated air-fuel ratio to adapt the parameters of the fuel injection algorithm.

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.

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.

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.

Advanced engine control and diagnosis strategies for internal combustion engines need accurate feedback information from the combustion engine. The feedback information can be utilized to control combustion features which allow the improvement of engine's efficiency through real-time control and diagnosis of the combustion process. This article describes a new method for combustion phase and IMEP estimation using one in-cylinder pressure and engine speed. In order to take torsional deflections of the crankshaft into account a gray-box model of the crankshaft is identified by subspace identification. The modeling accuracy is compared to a stiff physical crankshaft model. For combustion feature estimation, the identified MISO (multiple input single output) system is inverted. Experiments for a four-cylinder spark-ignition engine show the superior performance of the new method for combustion feature estimation compared to a stiff model approach.