Intelligent Energy Management in a Two Power-Bus Vehicle System

Abstract

In this paper we present an intelligent power controller for a vehicle power system that employs multiple power sources. In particular we focus on a vehicle power system architecture that is used in vehicles such as Mine Resistant Ambush Protected (MRAP) vehicle. These vehicles are designed to survive IED (Improvised Explosive Devices) attacks and ambushes. The power system has the following major components: a "clean" bus, a "dirty" bus, an engine, a hydraulic system and a switch between the clean and the dirty bus. We developed algorithms for intelligent energy management for this type of vehicle power system including DP (Dynamic Programming) optimization, DP online control and a machine learning technique that combines neural networks with DP to train an intelligent power controller. We present experiments conducted through modeling and simulation using a generic commercial software tool and a lab hardware setup.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2011
Accession Number
ADA547438

Entities

People

  • Abul Masrur
  • Chris Mi
  • Yi L. Murphey
  • Zheng Chen
  • Zhihang Chen

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Control Systems
  • Dynamic Programming
  • Electronic Equipment
  • Energy Management
  • Fuel Consumption
  • Improvised Explosive Devices
  • Inverters
  • Machine Learning
  • Neural Networks
  • Optimization
  • Power Supplies
  • Simulations
  • Systems Engineering

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Pulsed Power and Plasma Physics.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems