US 6,236,908 B1 · Virtual vehicle sensors based on neural networks trained using data generated by simulation models

Abstract

A virtual vehicle sensor includes a neural network which produces a sensor output based on a linear combination of non-linear physical signals generated by conventional physical sensors. Instead of determining an output directly, the neural network determines the polynomial coefficients as functions of the physical signals indicative of other engine operating parameters. The sensor is manufactured using relatively limited data collection to calibrate a simulation model. The output of the simulation model is used for model-based mapping to generate more comprehensive maps used for training the neural network. The trained neural network is embedded in a controller and acts as the virtual sensor to monitor engine parameters which are difficult to measure or for which conventional physical sensors do not currently exist. The virtual sensor may be used to sense parameters such as in-cylinder residual mass fraction, emission levels, in-cylinder pressure rise during combustion, and exhaust gas temperature.

Claims8

Dependent claims

A method of manufacturing a sensor for use with a vehicle component having a controller in communication with a plurality of physical sensors each generating a signal indicative of first operating parameters, the sensor determining values for a second operating parameter based on values for the plurality of first operating parameters, the method comprising:

generating test data during operation of the vehicle component representative of values for the plurality of first operating parameters for a first set of operating conditions;
calibrating a simulator for simulating operation of the vehicle component using the test data;
generating at least one map which characterizes performance of the vehicle component as a function of predetermined parameters, the map being based on output of the simulator for a second set of operating conditions;
adjusting weights corresponding to nodes of a neural network based on the at least one map so as to develop a trained neural network;
and
embedding the trained neural network into the controller by storing a representation of the trained neural network in computer readable media, the representation including a plurality of instructions executable by a microprocessor and data representing the weights corresponding to the nodes of the neural network, such that the trained neural network determines values for the second operating parameter based on values for the plurality of first operating parameters.

3 more elements

Dependencies are inferred from the claim text.

Virtual vehicle sensors based on neural networks trained using data generated by simulation models

Life of this patent

Virtual vehicle sensors based on neural networks trained using data generated by simulation models

Life of this patent

Abstract

Claims8