ECMS as a realization of Pontryagin's minimum principle for HEV control

Serrao, Lorenzo; Onori, Simona; Rizzoni, Giorgio

doi:10.1109/acc.2009.5160628

Cited by 351 publications

(226 citation statements)

References 12 publications

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“…It has been shown in [26], that under very mild and verifiable conditions, the optimal values of the dual optimization problem (18) and (19) and the primal optimization problem (15) are the same.…”

Section: Distributed Solution Using a Dual Decompositionmentioning

confidence: 99%

“…We therefore apply ideas from distributed optimization and will show that this leads to several linearly constrained quadratic programs (LCQPs). It should be noted that the subsystems in (15) are only connected by (15f).…”

Section: Distributed Solution Using a Dual Decompositionmentioning

confidence: 99%

“…Examples of online solution strategies that are real-time implementable are rule-based strategies (see, e.g., [13,14]), equivalent consumption minimization strategies (ECMS; see, e.g., [15][16][17]) and solution strategies based on model predictive control (MPC; see, e.g., [18][19][20]). The MPC strategies are interesting as they naturally take prediction information into account.…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Distributed Economic Model Predictive Control for Complete Vehicle Energy Management

et al. 2017

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Abstract:In this paper, a real-time distributed economic model predictive control approach for complete vehicle energy management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving several smaller optimization problems. The receding horizon control problem is formulated with variable sample intervals, allowing for large prediction horizons with only a limited number of decision variables and constraints in the optimization problem. Furthermore, a novel on/off control concept for the control of the refrigerated semi-trailer, the air supply system and the climate control system is introduced. Simulation results on a low-fidelity vehicle model show that close to optimal fuel reduction performance can be achieved. The fuel reduction for the on/off controlled subsystems strongly depends on the number of switches allowed. By allowing up to 15-times more switches, a fuel reduction of 1.3% can be achieved. The approach is also validated on a high-fidelity vehicle model, for which the road slope is predicted by an e-horizon sensor, leading to a prediction of the propulsion power and engine speed. The prediction algorithm is demonstrated with measured ADASIS information on a public road around Eindhoven, which shows that accurate prediction of the propulsion power and engine speed is feasible when the vehicle follows the most probable path. A fuel reduction of up to 0.63% is achieved for the high-fidelity vehicle model.

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Section: Distributed Solution Using a Dual Decompositionmentioning

confidence: 99%

Section: Distributed Solution Using a Dual Decompositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real-Time Distributed Economic Model Predictive Control for Complete Vehicle Energy Management

et al. 2017

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“…It is assumed that the model shown in Figure 5 is equivalent to a cascade system of an ideal voltage source and a resistance. Normally, the resistance and open circuit voltage are a function of SoC, which can be represented as Equations (16) and (17). …”

Section: Battery Modelmentioning

confidence: 99%

A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI

Zhang

Liu

et al. 2016

Energies

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This paper presents a new energy management system based on equivalent consumption minimization strategy (ECMS) for hybrid electric vehicles. The aim is to enhance fuel economy and impose state of charge (SoC) charge-sustainability. First, the relationship between the equivalent factor (EF) of ECMS and the co-state of pontryagin's minimum principle (PMP) is derived. Second, a new method of implementing the adaptation law using fuzzy proportional plus integral (PI) controller is developed to adjust EF for ECMS in real-time. This adaptation law is more robust than one with constant EF due to the variation of EF as well as driving cycle. Finally, simulations for two driving cycles using ECMS are conducted as opposed to the commonly used rule-based (RB) control strategy, indicating that the proposed adaptation law can provide a promising blend in terms of fuel economy and charge-sustainability. The results confirm that ECMS with Fuzzy PI adaptation law is more robust than ECMS with constant EF as well as PI adaptation law and it achieves significant improvements compared with RB in terms of fuel economy, which is enhanced by 4.44% and 14.7% for china city bus cycle and economic commission of Europe (ECE) cycle, respectively.

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“…The ECMS of local cost function optimization was first proposed by [24] for a HEV and later refined and extended within a number of research publications [9,[25][26][27][28]. For a given value of driver demand power P dmd , optimization of the energy consumption within the PHEV is achieved by selecting the optimal instantaneous power split (β) between the ICE (P ICE ) and HV battery (P B ) while adhering to the minimum and maximum power constraints within the PHEV: (24) …”

Section: Improved Equivalent Consumption Minimization Strategy (Ecms)mentioning

confidence: 99%

The Novel Application of Optimization and Charge Blended Energy Management Control for Component Downsizing within a Plug-in Hybrid Electric Vehicle

2012

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Abstract:The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialization. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Contained within this paper is an optimization study in which a charge blended strategy is used to facilitate the downsizing of the electrical machine, the internal combustion engine and the high voltage battery. An improved Equivalent Consumption Method has been used to manage the optimal power split within the powertrain as the PHEV traverses a range of different drivecycles. For a target CO 2 value and drivecycle, results show that this approach can yield significant downsizing opportunities, with cost reductions on the order of 2%-9% being realizable.Keywords: PHEV; battery; energy management; equivalent consumption minimization strategy (ECMS); component sizing; optimization 4895Number of cells in series Vehicle velocity (km/h) Slope of the road (-) Power split ratio Equivalence ratio for battery fuel consumption (-)

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ECMS as a realization of Pontryagin's minimum principle for HEV control

Cited by 351 publications

References 12 publications

Real-Time Distributed Economic Model Predictive Control for Complete Vehicle Energy Management

Real-Time Distributed Economic Model Predictive Control for Complete Vehicle Energy Management

A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI

The Novel Application of Optimization and Charge Blended Energy Management Control for Component Downsizing within a Plug-in Hybrid Electric Vehicle

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