| 摘要 |
<p>The invention relates to a method for a combustion engine using a neural net controlling the primary values, preferably ignition timing or amount of fuel but also the charge pressure, and a learning system for the neural net used. By using at least engine speed and engine load as input signals supplied to a neural net, and learning the neural net to create the necessary value for the primary value in concern dependent of the input parameters, is a smoother control of the combustion engine obtained without steep transitions between different operating cases. The control based upon a neural net exhibit considerable advantages compared to the conventional method having current amount of fuels or ignition timings of interest stored in a map containing primary values thereof. The neural net is trained by using a temporary connected learning computer (10) having an additional linear lambda sensor (5), and the current value of the primary value calculated by the learning computer is used as a target value when optimising the weight factors of the neural net, which optimisation is performed in order to reduce the deviation between the output signal from the neural net and the output signal from the learning computer. When disconnecting the learning computer, which is done when the learning process of the neural net is completed and the deviation is within acceptable limits, is a switch device (12) connecting the neural net for further control of the primary value.</p> |
