Stochastic Dynamic Programming in the Real-World Control of Hybrid Electric Vehicles

Vagg, Christopher; Akehurst, Sam; Brace, Chris; Ash, Lloyd

doi:10.1109/tcst.2015.2498141

Cited by 80 publications

(31 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The future power demand can be formulated as a discrete-time Markov decision process and can be modeled as a stochastic model established by Markov chain or Monte Carlo method, which reflects the probability distribution of the future power demand and the variation of the future driving cycles. In [87], a novel cost function (incorporating the square of battery charge) with a penalty on high-powered systems was used to lessen the affliction of real-world concerns such as battery health and motor temperature. Furthermore, a Markov chain was augmented with the information regarding SOC transitions to complete a full-state transition probability matrix, and the interpolation was used to distribute each state transition between multiple transition probabilities.…”

Section: Stochastic Dynamic Programming (Sdp)mentioning

confidence: 99%

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Kong

Liang

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

This paper presents a comprehensive review of energy management control strategies utilized in hybrid electric vehicles (HEVs). These can be categorized as rule-based strategies and optimization-based strategies. Rule-based strategies, as the most basic strategy, are widely used due to their simplicity and practical application. The focus of rule-based strategies is to determine and optimize the optimal threshold for mode switching; however, they fall into a local optimal solutions. To have better performance in energy management, optimization-based strategies were developed. The categories of the existing optimization-based strategies are identified from the latest literature, and a brief study of each strategy is discussed, which consists of the main research ideas, the research focus, advantages, disadvantages and improvements to ameliorate optimality and real-time performance. Deterministic dynamic programming strategy is regarded as a benchmark. Based on neural network and the large data processing technology, data-driven strategies are put forward due to their approximate optimality and high computational efficiency. Finally, the comprehensive performance of each control strategy is analyzed with respect to five aspects. This paper not only provides a comprehensive analysis of energy management control strategies for HEVs, but also presents the emphasis in the future.

show abstract

Section: Stochastic Dynamic Programming (Sdp)mentioning

confidence: 99%

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Kong

Liang

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Various optimization based EMS have been studied in this paper for energy management strategies in HEV [12]- [20]. Using maximum power search algorithm, engine operating points based on efficiency map of engine and generator, efficiency of battery is found out.…”

Section: B Optimization Based Emsmentioning

confidence: 99%

Examination on Classification of EVs and Energy Management Strategies of HEV

2019

IJITEE

View full text Add to dashboard Cite

In recent days, the demand for petroleum and emission of pollutant gases continuously increase. This necessitates the electrification power train which replaces Internal Combustion Engine (ICE). Despite pure electric vehicles or Battery Electric Vehicle (EV) reduce the greenhouse gas emissions, there are some major hurdles for EVs to overcome before they totally relieve ICE vehicles form transport sector such as range anxiety, battery storage, economic fall down due to automobile industries, etc. This necessitates Hybrid Electric vehicle (HEV) which combines two different power sources to propel the vehicle. One of the challenges in HEV is how to control the power coming from the two different sources such as battery and ICE. The prime goal of an Energy Management Strategy (EMS) is to manage energy flow such that fuel consumption and emissions are minimized without affecting the vehicle’s performance. In this paper, the different structures of power train and energy management strategies are analysed.

show abstract

“…Stochastic Differential Equations (SDE) in financial mathematics and economics have been extensively investigated [1][2][3][4][5][6]. Also, the effect of stochastic factors in science and mechanical and electronic engineering has been considered [7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A Case Study on Designing a Sliding Mode Controller to Stabilize the Stochastic Effect of Noise on Mechanical Structures: Residential Buildings Equipped with ATMD

Azizi

2020

Complexity

View full text Add to dashboard Cite

This study aims to stabilize the unwanted fluctuation of buildings as mechanical structures subjected to earth excitation as the noise. In this study, the ground motion is considered as a Wiener process, in which the governing stochastic differential equations have been presented in the form of Ito equation. To stabilize the vibration of the system, the ATMD system is considered and located on the upmost story of the building. A sliding mode controller has been utilized to control the ATMD system, which is a robust controller in the presence of uncertainty. For this purpose, the design of a sliding mode controller for the general dynamic system with Lipschitz nonlinearity and considering the Ito relations has been accomplished. The mentioned design has been implemented considering the presence of the Weiner process and existence of uncertainty in the structure and actuator. Then, the obtained general control law has been generalized to control the ATMD system. The results show that the designed controller is effective to reduce the effect of the unwanted impused vibrations on the building.

show abstract

Stochastic Dynamic Programming in the Real-World Control of Hybrid Electric Vehicles

Abstract: This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

Cited by 80 publications

References 31 publications

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Examination on Classification of EVs and Energy Management Strategies of HEV

A Case Study on Designing a Sliding Mode Controller to Stabilize the Stochastic Effect of Noise on Mechanical Structures: Residential Buildings Equipped with ATMD

Contact Info

Product

Resources

About