Modelling and control of a medium-duty hybrid electric truck

Lin, C.C.; Filipi, Zoran; Louca, Loucas S.; Peng, Huei; Assanis, Dennis N.; Stein, Jeffrey L.

doi:10.1504/ijhvs.2004.005455

Cited by 52 publications

(41 citation statements)

References 15 publications

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“…torque converter, transmission, differential etc, covering up to hybrid truck operation. An extended set of simulations was carried out for truck acceleration or Transient Cycles studies [55][56][57]. They also investigated the effect of various parameters on the vehicle and engine transient response with emphasis on VGT systems.…”

Section: Historical Overviewmentioning

confidence: 99%

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Review of Thermodynamic Diesel Engine Simulations under Transient Operating Conditions

Rakopoulos¹,

Giakoumis²

2006

SAE Technical Paper Series

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Study and modeling of transient operation is an important scientific objective. This is due to the fact that the majority of daily vehicle driving conditions involve transient operation, with non-linear situations experienced during engine transients. Thus, proper interconnection is needed between engine, governor, fuel pump, turbocharger and load. This paper surveys the publications available in the open literature concerning diesel engine simulations under transient operating conditions. Only those models that include both full engine thermodynamic calculations and dynamic powertrain modeling are taken into account, excluding those that focus on control design and optimization. Most of the attention is concentrated to the simulations that follow the filling and emptying modeling approach. A historical overview is given covering, in more detail, research groups with continuous and consistent study of transient operation. One of the main purposes of this paper is to summarize basic equations and modeling aspects concerning in-cylinder calculations, friction, turbocharger, engine dynamics, governor, fuel pump operation, and exhaust emissions during transients. The various limitations of the models are discussed together with the main aspects of transient operation (e.g. turbocharger lag, combustion and friction deterioration), which diversify it from the steady-state. Some of the most important findings in the field during the last 30 years are presented and discussed. The survey extends to special cases of transient diesel engine simulation, such as second-law analysis, response when the turbocharger compressor experiences surge, and whole vehicle performance. Several methods of improving transient response are also mentioned, based on the various simulations. An easy-to-read tabulation of all research groups dealing with the subject, that includes details about each model developed and engines/parameters studied, is also provided at the end of the paper.

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Section: Historical Overviewmentioning

confidence: 99%

“…A slightly different approach, being in the middle of quasi-linear and filling and emptying modeling, has been also adopted [55,57,114,115]. Here, a o CA based thermodynamic code was used to generate a steadystate, multi-dimensional, look-up engine torque map.…”

Section: Combustionmentioning

confidence: 99%

Review of Thermodynamic Diesel Engine Simulations under Transient Operating Conditions

Rakopoulos¹,

Giakoumis²

2006

SAE Technical Paper Series

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“…An adaptive rule-based power management for optimization of both energy use and emissions is also mentioned. In the case of hybrid vehicles, which involve multi-variables and/or multi-objectives, rules that cover all important trade-offs among different optimization objectives are difficult to design, and therefore, in [14], dynamic programming (DP) is used to understand the deficiency of rules and to serve as a reference to construct improved rules in terms of a fuel economy-emissions optimization problem. In [15], a two-mode, low and high level controller design is considered, which is subjected to an offline control variables' optimization in terms of fuel consumption minimization.…”

Section: Introductionmentioning

confidence: 99%

“…Optimization in HEVs often involves multi-objectives [14], and for a multi-objective optimization problem where the objectives are conflicting, multi-objective genetic algorithms are considered suitable [25], as they search for a Pareto optimal set. In [25], the two conflicting objectives of fuel consumption minimization and sizing were considered.…”

Section: Introductionmentioning

confidence: 99%

Optimal Rule-Based Power Management for Online, Real-Time Applications in HEVs with Multiple Sources and Objectives: A Review

Moulik

Söffker

2015

Energies

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The field of hybrid vehicles has undergone intensive research and development, primarily due to the increasing concern of depleting resources and increasing pollution. In order to investigate further options to optimize the performance of hybrid vehicles with regards to different criteria, such as fuel economy, battery aging, etc., a detailed state-of-the-art review is presented in this contribution. Different power management and optimization techniques are discussed focusing on rule-based power management and multi-objective optimization techniques. The extent of rule-based power management and optimization in solving battery aging issues is investigated along with an implementation in real-time driving scenarios where no pre-defined drive cycle is followed. The goal of this paper is to illustrate the significance and applications of rule-based power management optimization based on previous contributions.

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“…A number of methodologies have been proposed for development of control strategies, ranging from rule-based, to Equivalent Consumption Minimization Strategy [1], [2], fuzzy logic [3], [4], and horizon optimization [5], [6], [7], [8], [9]. The nature of the series hybrid system, with the engine decoupled from the wheels, allows significant freedom in designing the supervisory control strategy.…”

Section: Introductionmentioning

confidence: 99%

Self-Learning Neural Controller for Hybrid Power Management Using Neuro-Dynamic Programming

Johri

Filipi

2011

SAE Technical Paper Series

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A supervisory controller strategy for a hybrid vehicle coordinates the operation of the two power sources onboard of a vehicle to maximize objectives like fuel economy. In the past, various control strategies have been developed using heuristics as well as optimal control theory. The Stochastic Dynamic Programming (SDP) has been previously applied to determine implementable optimal control policies for discrete time dynamic systems whose states evolve according to given transition probabilities. However, the approach is constrained by the curse of dimensionality, i.e. an exponential increase in computational effort with increase in system state space, faced by dynamic programming based algorithms. This paper proposes a novel approach capable of overcoming the curse of dimensionality and solving policy optimization for a system with very large design state space. We propose developing a supervisory controller for hybrid vehicles based on the principles of reinforcement learning and neuro-dynamic programming, whereby the costto-go function is approximated using a neural network. The controller learns and improves its performance over time. The simulation results obtained for a series hydraulic hybrid vehicle over a driving schedule demonstrate the effectiveness of the proposed technique.

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Modelling and control of a medium-duty hybrid electric truck

Cited by 52 publications

References 15 publications

Review of Thermodynamic Diesel Engine Simulations under Transient Operating Conditions

Review of Thermodynamic Diesel Engine Simulations under Transient Operating Conditions

Optimal Rule-Based Power Management for Online, Real-Time Applications in HEVs with Multiple Sources and Objectives: A Review

Self-Learning Neural Controller for Hybrid Power Management Using Neuro-Dynamic Programming

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