Development of control strategies to optimize the fuel economy of hybrid electric vehicles

This thesis (1) reports a new Dynamic Programming (DP) approach, and (2) reports a Real Time Control strategy to optimize the energy management of a Hybrid Electric Vehicle(HEV). Increasing environmental concerns and rise in fuel prices in recent years has escalated interest in fuel efficient vehicl...

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Main Author: Ramaswamy, Nikhil
Other Authors: Sadegh, Nader
Format: Others
Language:en_US
Published: Georgia Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1853/51887
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spelling ndltd-GATECH-oai-smartech.gatech.edu-1853-518872014-10-07T03:33:41ZDevelopment of control strategies to optimize the fuel economy of hybrid electric vehiclesRamaswamy, NikhilModeling and simulationControl strategiesHybrid electric vehiclesHybrid electric carsDynamic programmingControl thoeryThis thesis (1) reports a new Dynamic Programming (DP) approach, and (2) reports a Real Time Control strategy to optimize the energy management of a Hybrid Electric Vehicle(HEV). Increasing environmental concerns and rise in fuel prices in recent years has escalated interest in fuel efficient vehicles from government, consumers and car manufacturers. Due to this, Hybrid electric vehicles (HEV) have gained popularity in recent years. HEV’s have two degrees of freedom for energy flow controls, and hence the performance of a HEV is strongly dependent on the control of the power split between thermal and electrical power sources. In this thesis backward-looking and forward-looking control strategies for two HEV architectures namely series and parallel HEV are developed. The new DP approach, in which the state variable is not discretized, is first introduced and a theoretical base is established. We then prove that the proposed DP produces globally optimal solution for a class of discrete systems. Then it is applied to optimize the fuel economy of HEV's. Simulations for the parallel and series HEV are then performed for multiple drive cycles and the improved fuel economy obtained by the new DP is compared to existing DP approaches. The results are then studied in detail and further improvements are suggested. A new Real Time Control Strategy (RTCS) based on the concept of preview control for online implementation is also developed in this thesis. It is then compared to an existing Equivalent Cost Minimization Strategy (ECMS) which does not require data to be known apriori. The improved fuel economy results of the RTCS for the series and parallel HEV are obtained for standard drive cycles and compared with the ECMS resultsGeorgia Institute of TechnologySadegh, Nader2014-05-22T15:33:21Z2014-05-22T15:33:21Z2014-052014-04-04May 20142014-05-22T15:33:21ZThesisapplication/pdfhttp://hdl.handle.net/1853/51887en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic Modeling and simulation
Control strategies
Hybrid electric vehicles
Hybrid electric cars
Dynamic programming
Control thoery
spellingShingle Modeling and simulation
Control strategies
Hybrid electric vehicles
Hybrid electric cars
Dynamic programming
Control thoery
Ramaswamy, Nikhil
Development of control strategies to optimize the fuel economy of hybrid electric vehicles
description This thesis (1) reports a new Dynamic Programming (DP) approach, and (2) reports a Real Time Control strategy to optimize the energy management of a Hybrid Electric Vehicle(HEV). Increasing environmental concerns and rise in fuel prices in recent years has escalated interest in fuel efficient vehicles from government, consumers and car manufacturers. Due to this, Hybrid electric vehicles (HEV) have gained popularity in recent years. HEV’s have two degrees of freedom for energy flow controls, and hence the performance of a HEV is strongly dependent on the control of the power split between thermal and electrical power sources. In this thesis backward-looking and forward-looking control strategies for two HEV architectures namely series and parallel HEV are developed. The new DP approach, in which the state variable is not discretized, is first introduced and a theoretical base is established. We then prove that the proposed DP produces globally optimal solution for a class of discrete systems. Then it is applied to optimize the fuel economy of HEV's. Simulations for the parallel and series HEV are then performed for multiple drive cycles and the improved fuel economy obtained by the new DP is compared to existing DP approaches. The results are then studied in detail and further improvements are suggested. A new Real Time Control Strategy (RTCS) based on the concept of preview control for online implementation is also developed in this thesis. It is then compared to an existing Equivalent Cost Minimization Strategy (ECMS) which does not require data to be known apriori. The improved fuel economy results of the RTCS for the series and parallel HEV are obtained for standard drive cycles and compared with the ECMS results
author2 Sadegh, Nader
author_facet Sadegh, Nader
Ramaswamy, Nikhil
author Ramaswamy, Nikhil
author_sort Ramaswamy, Nikhil
title Development of control strategies to optimize the fuel economy of hybrid electric vehicles
title_short Development of control strategies to optimize the fuel economy of hybrid electric vehicles
title_full Development of control strategies to optimize the fuel economy of hybrid electric vehicles
title_fullStr Development of control strategies to optimize the fuel economy of hybrid electric vehicles
title_full_unstemmed Development of control strategies to optimize the fuel economy of hybrid electric vehicles
title_sort development of control strategies to optimize the fuel economy of hybrid electric vehicles
publisher Georgia Institute of Technology
publishDate 2014
url http://hdl.handle.net/1853/51887
work_keys_str_mv AT ramaswamynikhil developmentofcontrolstrategiestooptimizethefueleconomyofhybridelectricvehicles
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