Trained neural network engine idle speed control system

Claim 1

Apparatus for controlling the idle speed of an internal combustion engine, said engine including an ignition timing control and a throttle, said apparatus comprising, in combination: sensing means coupled to said engine for producing a plurality of input signal values, each of which is indicative of a corresponding one of a plurality of engine operation conditions, said conditions including engine speed and the rate at which intake air is being delivered to said engine. data storage means for storing a neural network definition data structure which defines a neural network, said structure including: signal value data defining said input signal values and the values of signals being processed by said neural network, and weight values governing the manner in which signals are combined within said neural network, and processing means consisting of an electronic engine control microprocessor and program storage means for storing instructions executable by said processor, said processing means including: means responsive to said signal value data in said data structure for performing a generic neural network routine for combining selected signal values to produce and store new signal values in said data structure in accordance with said weight values in said data structure, output means coupled to said throttle and responsive to one or more of said now signal values for controlling the speed of said engine, second output means coupled to said ignition timing control and responsive to one or more of said new signals for generating, a second output signal for controlling the ignition timing of said engine, and an independently operating training processor external to said electronic engine control microprocessor.

Claim 8

The method of training a neural network to control the idle speed of an internal combustion engine, said neural network being implemented by an electronic engine control processor connected to receive input signal values indicative of the operating speed of said engine and the rate at which intake air is being delivered to said engine, and being further connected to supply output signals to control the speed of said engine, said method comprising the steps of: interconnecting an external training processor to said electronic engine control processor such that said external training processor can access said input signal values, generating and storing a data structure consisting of an initial set of neural network weight values, operating a representative internal combustion engine and its connected electronic engine control processor over a range of operating conditions, concurrently with the operation of said engine, executing a generic neural network control program on said electronic engine control processor to process said input signal values into output control values in accordance with the values stored in said data structures, concurrently with the operation of said engine, varying said output signals in accordance with said output control values to control the operation of said engine, concurrently with the operation of said engine, executing a neural network training program on said external training processor to progressively alter at least selected ones of said neural network weight values in said data structure to modify the results produced during the execution of said neural network training program, evaluating the operation of said engine to indicate deviations in the operating speed of said engine from a desired idle speed is achieved, and utilizing the values in said data structure determined to minimize said deviations to control the execution of said neural network control program on said EEC to control production engines corresponding to said representative engine.

Claim 9

The method of training a neural network to control the idle speed of an internal combustion engine, said neural network being implemented by an electronic engine control processor connected to receive input signal values indicative of the operating speed of said engine and the rate at which intake air is being delivered to said engine, and being further connected to supply output signals to control the speed of said engine, said method comprising the steps of: interconnecting an external training processor to said electronic engine control processor such that said external training processor can access said input signal values, generating and storing a data structure consisting of an initial set of neural network weight values, operating a representative internal combustion engine and its connected electronic engine control processor over a range of operating conditions, concurrently with the operation of said engine, executing a generic neural network control program on said electronic engine control processor to process said input signal values into output control values in accordance with the values stored in said data structures, concurrently with the operation of said engine, varying said output signals in accordance with said output control values to control the operation of said engine, concurrently with the operation of said engine, executing a neural network training program on said external training processor to progressively alter at least selected ones of said neural network weight values in said data structure to modify the results produced during the execution of said neural network training program, evaluating the operation of said engine to indicate deviations in the operating speed of said engine from a desired idle speed is achieved, and utilizing the values in said data structure determined to minimize said deviations to control the execution of said neural network control program on said EEC to control production engines corresponding to said representative engine.