Abstract:
A reliable alternative method of sensing the inlet air flow in a combustion chamber of a cylinder of an internal combustion engine and a relative sensing device that implements the method have been found. According to the method, the inlet air flow is assessed with soft-computing techniques basically exploiting a combustion pressure signal generated by a pressure sensor installed in the cylinder.
Abstract:
A probabilistic neural network, comprising a hidden layer of neurons, each computing respective membership matrix elements for an input vector of the neural network according to a respective radial basis function defined by a respective spread factor and according to the distance of the input vector from a respective constant vector, wherein said hidden layer comprises at least two neurons having different spread factors (S). A method of training the novel probabilistic neural network is also disclosed.
Abstract:
A method for estimating data of the state of a system, as well as the EKF filters, allows to use nonlinear mathematical models that describe the systems, but ensures a more accurate precision. This result is due to the fact that the method is based on the EKF technique, but it differs from the EKF technique for adapting it to work with a filter that implements a first degree Stirling approximation formula. This method may be used for estimating position and speed of a brushless motor and may be implemented in a relative device. Such a device may be used for controlling a brushless motor, or it may be introduced in the control loop of a brushless motor of a power steering system, in order to make the driver feel an antagonist torque on the steering wheel determined, according to a pre-established waveform, in function of the speed of the vehicle and of the steering angle. The disclosed methods may even be implemented via software by a program executed by a computer or a microprocessor.
Abstract:
A reliable an convenient alternative method of diagnosing misfire or partial combustion conditions in an internal combustion engine without using a phonic wheel and a relative diagnosis unit that implements the method have been found. The combustion conditions are discriminated with soft-computing techniques directly exploiting a combustion pressure signal generated by a common pressure sensor installed in the cylinder. There exists an exploitably close correlation between the instantaneous values of the internal cylinder pressure and the occurrence of misfire or partial combustion conditions, and thus the cylinder pressure signal may be reliably used for diagnosing misfires or partial combustions in any functioning condition of the engine.
Abstract:
The invention relates to a soft-computing method for establishing the dissipation law of the heat in a diesel Common Rail engine, in particular for establishing the dissipation mean speed (HRR) of the heat. The method provides the following steps:
choosing a number of Wiebe functions whereon a dissipation speed signal (HRR) of the heat is decomposed; applying a Transform Ψ to the dissipation speed signal (HRR) of the heat; carrying out analysis of homogeneity of the Transform Ψ output; realising a corresponding neural network MLP wherein the design is guided by an evolutive algorithm; making learn and testing the neural network MLP.
Abstract:
A control system (10) for an electromechanical-braking system (1) provided with actuator elements (2, 5) configured to actuate braking elements (6, 8) for exerting a braking action has a control stage (16) for controlling the braking action on the basis of a braking reference signal (w). The control stage comprises a model-based predictive control block (16), in particular of a generalized predictive self-adaptive control (GPC) type, operating on the basis of a control quantity (F b ) representing the braking action. The control system further has: a model-identification stage (14), which determines parameters (a, b, d) identifying a transfer function (G(z)) of the electromechanical-braking system (1); and a regulation stage (15), which determines an optimal value of endogenous parameters of the control system on the basis of the value of the identifying parameters.