Advanced Engine Control for Increasing Fuel Efficiency and Power Density While Reducing Observable Emissions From Military Diesel Engines

Abstract

Military diesel engines used in combat and tactical applications have their own specific engine control requirements that differ from those of commercial heavy-duty vehicles. The implementation of advanced engine control methods in diesel-powered military vehicles can result in an increase in their performance, a reduction in their fuel consumption, a reduction in their observable exhaust emissions and an improvement in their stealth capabilities. Neural network-based engine control has the potential to allow for the simultaneous, optimized control of several engine parameters such as fueling quantity, injection timing, injection pressure and turbocharger boost pressure. Future engines will be considerably more complicated in their control, incorporating such additional technologies as exhaust gas recirculation, variable geometry turbocharging, variable valve timing, multiple injection strategies and exhaust gas aftertreatment. The advanced engine control techniques developed here will facilitate the optimal control of these more sophisticated engines in future military applications.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA378776

Entities

People

  • Chris M. Atkinson
  • E. Hanzevack
  • G. J. Thompson
  • Nigel N. Clark
  • T. W. Long

Organizations

  • West Virginia University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Compression Ignition
  • Compression Ignition Engines
  • Diesel Engines
  • Engines
  • Exhaust Gases
  • Fuel Consumption
  • Fuel Efficiency
  • Gases
  • Heavy Duty
  • Measurement
  • Military Applications
  • Military Vehicles
  • Neural Networks
  • Recurrent Neural Networks
  • Vehicles
  • West Virginia

Readers

  • Internal Combustion Engine (ICE) Technology.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems