Hybrid electrical energy storage systems

Pedram, Massoud; Chang, Naehyuck; Kim, Younghyun; Wang, Yanzhi

doi:10.1145/1840845.1840924

Cited by 100 publications

(78 citation statements)

References 10 publications

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“…In [6], three HEES management problems are introduced: charge allocation, charge replacement, and charge migration. The charge allocation problem is, when energy comes from the external power source, to find the appropriate destination banks and energy amount that maximize the energy efficiency.…”

Section: Hybrid Electrical Energy Storage Systemsmentioning

confidence: 99%

“…In Figure 2, we control two independent variables, V CT I (t) and I CT I (t), at time t for given OCVs V OC src (t) and V OC dst (t), which can be derived through the SoC-OCV relation such as (6). We have dependent variables I src (t) and I dst (t) that can be determined accordingly by (1), as well as the converter efficiency introduced in Section 3.1.1.…”

Section: Formal Problem Statementmentioning

confidence: 99%

“…A simple structure of HEES systems is found in advanced electric vehicles, especially for efficient regenerative braking systems. More recently, generalized HEES systems are introduced [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Analogous to memory management in computer systems, the energy management issues in HEES systems can be broken into charge allocation, charge replacement, and charge migration operations [6]. Power sources (and load devices) have different characteristics in terms of energy/power capacity (and voltage/current requirements.)…”

Section: Introductionmentioning

confidence: 99%

“…Power sources (and load devices) have different characteristics in terms of energy/power capacity (and voltage/current requirements.) Moreover, the cycle efficiency and output power availability of each EES element may vary depending on a number of factors, including the SoC of the element, the rate at which energy is provided or extracted, and so on [6]. Therefore, it is crucial to provide policies for charge allocation to the best-suited EES element for a given incoming power source, and for charge replacement from the best-suited EES element for the load device.…”

Section: Introductionmentioning

confidence: 99%

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Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Wang¹,

Kim²,

Xie³

et al. 2011

IEEE/ACM International Symposium on Low Power Electronics and Design

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Electrical energy is high-quality form of energy, and thus it is beneficial to store the excessive electric energy in the electrical energy storage (EES) rather than converting into a different type of energy. Like memory devices, no single type of EES element can fulfill all the desirable requirements. Despite active research on the new EES technologies, it is not likely to have an ultimate high-efficiency, highpower/energy capacity, low-cost, and long-cycle life EES element in the near future. We propose an HEES system that consists of two or more heterogeneous EES elements, thereby realizing the advantages of each EES element while hiding their weaknesses. The HEES management problems can be broken into charge allocation into different banks of EES elements, charge replacement (i.e., discharge) from different banks of EES elements, and charge migration from one bank to another bank of EES elements.In spite of the optimal charge allocation and replacement, charge migration is mandatory to leverage the EES system efficiency. This paper is the first paper that formally describes the charge migration efficiency and its optimization. We first define the charge migration architecture and the corresponding charge migration problem. We provide a systematic solution for a single source and single destination charge migration considering the efficiency of the charger and power converter, the rate capacity effect of the storage element, the terminal voltage variation of the storage element as a function of the state of charge (SoC), and so on. Experimental results for an HEES system comprising of banks of batteries and supercapacitors demonstrate a migration efficiency improvement up to 51.3%, for supercapacitor to battery and supercapacitor to supercapacitor charge migration.

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Section: Hybrid Electrical Energy Storage Systemsmentioning

confidence: 99%

Section: Formal Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Wang¹,

Kim²,

Xie³

et al. 2011

IEEE/ACM International Symposium on Low Power Electronics and Design

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Hybrid Model Predictive Power Management of a Battery‐Supercapacitor Electric Vehicle

Meyer¹,

DeCarlo

Pekarek

2015

Asian Journal of Control

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Recently, battery powered electric vehicles (EV), such as the Tesla Model S, have reached commercialization. Future EVs will likely pair the battery with a supercapacitor to extend battery life by minimizing the effects of high power and rapidly fluctuating loads. As such, this paper investigates optimal power management of an EV powertrain with both a battery pack and a supercapacitor as energy sources. The battery‐supercapacitor‐based powertrain has four distinct controllable modes, each with a unique set of dynamics and constraints. Unique power flow expressions for the supercapacitor, vehicle motion, and drive system induction motor are presented. The overall powertrain is represented as a switched interconnected dynamical system having both differential and algebraic constraints in each mode of operation. Constrained by this model, this paper sets forth a hybrid model predictive control strategy for minimizing velocity tracking error and frictional braking (to encourage regenerative braking) while encouraging fast recharge of the supercapacitor. The optimization is performed using a relaxed representation of the control problem (termed the embedding method), collocation for discretization, and traditional nonlinear programming to compute the mode and continuous control inputs. The methodology avoids the computational complexity associated with alternative approaches such as mixed‐integer programming. The developed optimization methodology is shown to be useful as a rapid iterative prototyping tool by varying vehicle mass and electric drive maximum power to find combinations that result in satisfactory tracking performance of a trapezoidal drive profile. Performance of the originally specified powertrain and a first design iteration are compared using simulations of the EPA highway and urban drive profiles and the new European drive cycle to verify the first design iteration gives improvement.

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Energy Storage System Design for Green-Energy Cyber Physical Systems

Williamson

Shang

2013

Design Technologies for Green and Sustainable Computing Systems

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Hybrid electrical energy storage systems

Cited by 100 publications

References 10 publications

Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems

Hybrid Model Predictive Power Management of a Battery‐Supercapacitor Electric Vehicle

Energy Storage System Design for Green-Energy Cyber Physical Systems

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