Browse Prior Art Database

MODEL-BASED CONTROL FOR PERFORMANCE OPTIMIZATION OF IC ENGINES

IP.com Disclosure Number: IPCOM000248736D
Publication Date: 2017-Jan-03
Document File: 4 page(s) / 128K

Publishing Venue

The IP.com Prior Art Database

Abstract

The invention discloses a system and method to capture variations such as engine to engine, cylinder to cylinder, and over life of internal combustion engines to optimize performance. The system uses an engine performance model and model based control strategy to optimize specific fuel consumption, maximize power output, and continuously monitor engine health. The system uses dynamic models, suitably calibrated at the time of manufacture and periodically re-calibrated over life of the engine to predict key performance metrics of the engine like cylinder pressure, manifold pressures, temperatures, fuel efficiency, and emissions. The system is used to optimize engine performance using model-based control to balance cylinders, optimal injection timing, and exhaust gas recirculation, for each operating point to provide best fuel efficiency while ensuring emissions compliance. This can be used to ensure consistent transient performance with respect to emissions and power ramp up engine-to-engine. The system and method will also enable model-based diagnostics providing easier maintenance.

This text was extracted from a Microsoft Word document.
At least one non-text object (such as an image or picture) has been suppressed.
This is the abbreviated version, containing approximately 41% of the total text.

MODEL-BASED CONTROL FOR PERFORMANCE OPTIMIZATION OF IC ENGINES

BACKGROUND

The invention relates generally to internal combustion engines and operation thereof to meet environmental regulations. Optimization of emissions and fuel consumption in diesel locomotive engines is a particular problem. Every locomotive in a fleet has the same control configuration or recipe (and for every cylinder) over the life of the engine/locomotive and has fixed deration tables based on off-line testing on a single engine or a few pre-production engines/locomotives. The overall power output is fixed assuming conservative margins over the entire operating range. Due to manufacturing tolerances, component variations and vendor variations, each diesel engine coming out of the assembly line will not behave the same way. There will be engine-to-engine variations in terms of emissions and fuel efficiency. This results in non-optimized (power/emissions) engine operation leading to higher fuel consumption and/or higher unreliability. Further, over the life of an engine, typically, the cylinder imbalance is expected to get worse due to soot accumulation and uneven wear of valves, injectors etc. There is therefore a need to assess the performance and health of the engine/engine component(s) to operate the engine in compliance with emissions regulations while deriving best efficiency and performance - both at the time of engine manufacture (as-new engine) and over the entire life of the engine.

BRIEF DESCRIPTION OF DRAWINGS

The invention discloses a system and method for model-based optimization of internal combustion engines, in which:

FIG. 1 shows a system for model-based control of internal combustion engines.

FIG. 2 shows a method of controlling engine performance using a model.

DETAILED DESCRIPTION

The invention discloses a system and method to capture the variation (e.g., engine to engine, cylinder to cylinder, and over life) through individual engine calibration when new and at frequent/periodic time steps/intervals. The system as illustrated in FIG. 1 uses an engine performance model and model-based control strategy to optimize specific fuel consumption (SFC), maximize power output, and continuously monitor engine health.

The system uses dynamic models of a diesel engine, suitably calibrated at the time of manufacture and periodically re-calibrated over life of the engine to predict key performance metrics of the engine like cylinder pressure, manifold pressures, temperatures, fuel efficiency, and emissions. The baseline model is a combination of lumped physics models and black box (data based) models. The black box models predict engine parameters such as indicated efficiency, volumetric efficiency, etc. These black box models are calibrated to a standard engine dataset. The baseline model is then made into a per asset/engine model by calibrating either on-line or off-line using available sensor measurements, as shown in FIG. 1. The data driven emissions model (NOX...