Modeling of a Hydraulic Energy Regeneration System: Part I—Analytical Treatment

Résumé -Propulsion hybride hydraulique des poids lourds : une approche alliant les techniques de simulation et d'« Engine-In-the-loop » (EIL) afin de maximiser les économies de carburant et les avantages en termes d'émissions-La situation énergétique mondiale, la dépendance du secteur des transports vis-à-vis des combustibles d'origine fossile et la nécessité d'une réponse rapide face au défi présenté par le réchauffement climatique fournissent une forte motivation pour le développement de moyens de propulsion véhiculaires économes. Pour les camions, cette tâche est particulièrement difficile à accomplir du fait d'importantes contraintes de taille et de poids. L'hybridation est la seule approche qui puisse déboucher sur des progrès importants à court et moyen termes. En particulier, la configuration "hybride série" découple le moteur thermique des roues et permet une flexibilité complète dans le contrôle des points de fonctionnement moteur. De plus, la conversion et le stockage de l'énergie hydraulique fournissent une densité de puissance et un rendement excellents. Le défi technologique tient à la faible densité d'énergie de l'accumulateur hydraulique, et met en avant l'importance particulière du développement du gestionnaire de l'énergie. Il est communément admis qu'il faut maintenir le moteur au point de rendement maximum mais, si l'objectif ultime en terme énergétique consiste à optimiser drastiquement le rendement du moteur, ceci induit des phases transitoires fréquentes causant pour des moteurs diesels des effets opposés tant sur l'émission de particules que sur l'agrément de conduite. Par conséquent, nous proposons une méthodologie pour le superviseur d'énergie d'un système hybride, qui prend en compte 2 objectifs : la réduction de consommation et la réduction des émissions polluantes. Les économies de carburant sont prises en compte par une approche fondée sur la simulation, alors que l'étude de l'impact des phases transitoires du moteur sur les émissions de particules, est fondée sur un dispositif expérimental combinant modèles temps réel et moteur réel -l'EIL (Engine-In-the-Loop). Le dispositif EIL confirme que le contrôle de la répartition énergétique thermique/hydraulique de l'état de charge des batteries (SOC) présente des avantages certains sur celui basé sur l'approche de contrôle type « bang-bang ». De plus, elle démontre la capacité de l'Hybride Hydraulique Série à améliorer de 72 % les économies de carburant d'un camion de taille moyenne tout en réduisant les émissions de particules de 74 % comparée á la référence conventionnelle sur le cycle de conduite urbain.

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“…The hydraulic pump/motor model is an updated version of Wilson's P/M theory [20]. The P/M is an axial piston variable displacement type.…”

Section: Modeling the Components And Subsystemsmentioning

confidence: 99%

Hydraulic Hybrid Propulsion for Heavy Vehicles: Combining the Simulation and Engine-In-the-Loop Techniques to Maximize the Fuel Economy and Emission Benefits

Filipi

Kim

2009

Oil & Gas Science and Technology

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“…S ince increased heat capacity generally improves accumulator efficiency, the effect of elastomeric foam added to the gas side is considered and modeled based on [ 10]. The internal friction and the pressure losses at the inlet/outlet and along the connecting hoses are also included in the accumulator model [ 8]. Typically, the accumulator average efficiency calculated based on the ratio of total energy flowing in and out is within 95~97%.…”

Section: Modeling the Hydraulic Hybrid Propulsion Systemmentioning

confidence: 99%

“…The hydraulic pump/motor model is derived from the concepts proposed by Pourmovahed et al [8]. The model accounts for both volumetric and torque losses in the pump/motor.…”

Section: Modeling the Hydraulic Hybrid Propulsion Systemmentioning

confidence: 99%

Optimal Power Management for a Hydraulic Hybrid Delivery Truck

Lin

Filipi³

et al. 2004

Vehicle System Dynamics

190

132

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SUMMARYHydraulic hybrid propulsion and energy storage components demonstrate characteristics that are very different from their electric counterparts, thus requiring unique control strategies. This paper presents a methodology for developing a power management strategy tailored specifically to a parallel Hydraulic Hybrid Vehicle (HHV) configured for a medium-size delivery truck.The Hydraulic H ybrid Vehicle is modelled in the MATLAB/SIMULINK environment to facilitate system integration and control studies . A Dynamic Programming (DP) algorithm is used to obtain optimal control actions for gear shifting and power splitting bet ween the engine and the hydraulic motor over a representative urban driving schedule . Features of optimal trajectories are then studied to derive i mplementable rules . System behaviour demonstrates that the new control strategy takes advantage of high power density and efficiency characteristics of hydraulic components, and minimizes disadvantages of low energy density, to achieve enhanced overall efficiency . Simulation results indicate that the potential for fuel economy improvement of medium trucks with hydraulic hybrid propulsion can be as high as 48 %.

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“…The hydraulic pump/motor model is an updated version of Wilson's P/M theory [28]. The P/M is an axial piston variable displacement type.…”

Section: Hybrid Vehicle Supervisory Controller Problemmentioning

confidence: 99%

“…The net pressure difference between accumulator and reservoir pressure is the head pressure on pump and motors. Modeling of the accumulator and the reservoir is based on the application of the energy conservation equation to the gas, as proposed by Pourmovahed and Otis [28]. The accumulator is modeled with elastomeric foam on the gas side to increase the thermal time constant to increase thermal capacity and reduce heat loss [29].…”

Section: Hybrid Vehicle Supervisory Controller Problemmentioning

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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Modeling of a Hydraulic Energy Regeneration System: Part I—Analytical Treatment

Cited by 84 publications

References 0 publications

Hydraulic Hybrid Propulsion for Heavy Vehicles: Combining the Simulation and Engine-In-the-Loop Techniques to Maximize the Fuel Economy and Emission Benefits

Hydraulic Hybrid Propulsion for Heavy Vehicles: Combining the Simulation and Engine-In-the-Loop Techniques to Maximize the Fuel Economy and Emission Benefits

Optimal Power Management for a Hydraulic Hybrid Delivery Truck

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

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