Calibration of online real-world systems using simulations
AssigneeSparkcognition, Inc.
InventorsElad Liebman, Sridhar Sudarsan
Life of this patent
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Abstract
Calibration of online combustion engines using simulations, including: simulating, on a processor coupled to an engine and based on operation data generated during operation of the engine, operation of the engine; training, based on simulating the operation of the engine, one or more trained models; and generating, based at least on the one or more trained models, calibration data corresponding to one or more electronically controllable components of the engine.
Claims19
A method comprising:
- simulating, on a processor coupled to an engine, based on operation data generated during operation of the engine and simulation output from simulating the engine during a prior offline period, operation of the engine;
- training, based on simulating the operation of the engine, one or more trained models;
- generating, based at least on the one or more trained models, calibration data corresponding to one or more electronically controllable components of the engine;
- transmitting, to a simulation learning environment that is independent of the vehicle, vehicle operation data collected during operation of the vehicle;
- receiving, from the simulation learning environment, one or more externally trained models based on simulating operation of the engine using the vehicle operation data;
- and
- generating, based on the one or more externally trained models, updated calibration data corresponding to the one or more electronically controllable components of the engine, wherein the updated calibration data includes both the one or more externally trained models and the one or more trained models based on simulating operation of the engine during operation of the engine.
A computer program product disposed upon a non-transitory computer-readable medium, the computer program product comprising computer program instructions that, when executed, cause a computer to carry out the steps of:
- simulating, on a processor coupled to an engine, based on operation data generated during operation of the engine and simulation output from simulating the engine during a prior offline period, operation of the engine;
- training, based on simulating the operation of the engine, one or more trained models;
- generating, based at least on the one or more trained models, calibration data corresponding to one or more electronically controllable components of the engine;
- transmitting, to a simulation learning environment that is independent of the vehicle, vehicle operation data collected during operation of the vehicle;
- receiving, from the simulation learning environment, one or more externally trained models based on simulating operation of the engine using the vehicle operation data;
- and
- generating, based on the one or more externally trained models, updated calibration data corresponding to the one or more electronically controllable components of the engine, wherein the updated calibration data includes both the one or more externally trained models and the one or more trained models based on simulating operation of the engine during operation of the engine.
A vehicle comprising:
- an engine comprising one or more electronically controllable components;
- a memory configured to store one or more trained models;
- and
- one or more processors configured to:
- simulate, based on operation data generated during operation of the engine and simulation output from simulating the engine during a prior offline period, operation of the engine;
- train, based on simulating the operation of the engine, the one or more trained models;
- generate, based at least on the one or more trained models, calibration data corresponding to the one or more electronically controllable components of the engine;
- transmit, to a simulation learning environment that is independent of the vehicle, vehicle operation data collected during operation of the vehicle;
- receive, from the simulation learning environment, one or more externally trained models based on simulating operation of the engine using the vehicle operation data;
- and
- generate, based on the one or more externally trained models, updated calibration data corresponding to the one or more electronically controllable components of the engine, wherein the updated calibration data includes both the one or more externally trained models and the one or more trained models based on simulating operation of the engine during operation of the engine.
Dependencies are inferred from the claim text.