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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.

Equipping low cost two-wheelers with engine management systems (EMS) enables not only a reduction of emissions but also an improvement in fuel consumption and system robustness. These benefits are accompanied by initially higher system costs compared to carburetor systems. Therefore, intelligent software solutions are developed by Bosch, which enable a reduction of the necessary sensors for a port fuel injection system (PFI) and furthermore provide new possibilities for combustion control. One example for these intelligent software solutions is a model based evaluation of the engine speed. By use of the information contained in the engine speed signal, characteristic features like air charge, indicated mean effective pressure (imep) and combustion phasing are derivable. The present paper illustrates how these features could be used to reduce the system costs and to improve fuel consumption and system robustness.

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.

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.

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.

Contemporary diesel engines are high-tech power plants that provide high torques at very good levels of efficiency. By means of modern injecting-systems such as Common-Rail Injection, combustion noise and emissions could be influenced positively as well. Diesel engine are therefore used increasingly in top-range and sports cars. Today's production ECUs have no or only very low feedback regarding the process in the combustion chamber. As long as this data is missing, the design of the maps in the ECU can only be a compromise, since production tolerances and aging processes have to be considered in advance. Disturbances in the combustion process may not be detected at all. If more knowledge about the course of combustion is provided, especially the start of combustion (SOC), various operating parameters, such as the pilot injection quantity or the beginning of current feed to the injector, could be adjusted more precisely and individually for every cylinder.

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.

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.

In the low-cost segment for 2-Wheelers legislative, economic and ecologic considerations necessitate a reduction of the emissions and further improvement in fuel consumption. To reach these targets, the commonly used carburetors are being replaced by engine management systems (EMS). One option to provide these systems for acceptable and attractive system costs is to save a sensor device and to substitute its measure by an estimation value. In many motorcycles the rotor of the vehicle's alternator is rigidly attached to the crankshaft. Therefore, the voltage and current signals of the alternator contain information about the engine's speed, which can be retrieved by evaluating these electric signals. After further processing of this information inside the electronic control unit (ECU), the absolute crankshaft position can be obtained. A high-resolution speed signal without mechanical distortions like tooth errors is gained, whose signal quality equals the one of a common speed sensor.