Performance evaluation of battery balancing hardware

Preindl, Matthias; Danielson, Claus; Borrelli, Francesco

doi:10.23919/ecc.2013.6669307

Cited by 33 publications

(20 citation statements)

References 18 publications

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“…The balancing currents which control the state of charge is Quu(t) where u(t) E [-l,l] m is the normalized balancing currents and Qu E jR m x m defines current capacities of each link [4] as follows o where I m axl ... I m axm are the maximum currents for link 1 to m respectively.…”

Section: S Ystem Descriptionmentioning

confidence: 99%

“…The topology matrix T defines how the balancing charge is transferred via the links [4]. This paper uses the cell to stack topology, which is defined by …”

Section: S Ystem Descriptionmentioning

confidence: 99%

“…In this work, we assume the SOC is reconstructed with sufficient precision. Balancing control can be implemented with different strate gies such as rule based approaches [12], optimization algo rithms [4] [13] and fuzzy logic [14]. In designing the LQR, we first need to transform (1) into a regulation problem using x = Lx where L is defined in [4] and the balanced state is when x = O.…”

Section: B High Level Controlmentioning

confidence: 99%

“…A non-dissipative approach uses power electronics to transfer charge between cells. Redistribu tive techniques and various hardware topologies have been studied and applied in industry [2] [3] [4]. The two main redistributive methods are cell to cell (C2C) which transfers charge between adjoining cells, cell to stack (C2S) which transfers charge from one cell to the entire stack and stack to cell (S2C) which is the opposite case of C2S by transferring the charge from the entire stack to just one cell.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Simplified control for redistributive balancing systems using bidirectional flyback converters

McCurlie

Preindl

Malysz

et al. 2015

2015 IEEE Transportation Electrification Conference and Expo (ITEC)

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Battery stacks with many cells per string require sophisticated balancing hardware for capacity maximization, safe operation, and extended lifetime. This paper proposes a sim plified control architecture for redistributive battery balancing topologies. A high level controller defines the link currents to be actuated by Ryback DC/DC converters. Linear transformations are used to rewrite the balancing problem as a regulation problem that can be solved with a saturated LQR. To reduce the overall system complexity and cost, the low-level control requirements are minimized using feedforward approaches based on pulse width and pulse frequency modulation. The control system is developed using MATLAB/SimulinkIPLECS and validated experimentally.

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Section: S Ystem Descriptionmentioning

confidence: 99%

“…The topology matrix T defines how the balancing charge is transferred via the links [4]. This paper uses the cell to stack topology, which is defined by …”

Section: S Ystem Descriptionmentioning

confidence: 99%

Section: B High Level Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simplified control for redistributive balancing systems using bidirectional flyback converters

McCurlie

Preindl

Malysz

et al. 2015

2015 IEEE Transportation Electrification Conference and Expo (ITEC)

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“…The superiority over passive balancing in terms of energy efficiency and speed has been proven in theory ( [2], [3], [4]) and by measurement (see references in Table 1 and [5], [6], [7]). Despite the advantages, battery systems with active balancing are still rare in industrial applications.…”

Section: Introductionmentioning

confidence: 99%

A Novel Non-Isolated Active Charge Balancing Architecture for Lithium-Ion Batteries

Räber

Hink

Heinzelmann

et al. 2018

2018 IEEE 27th International Symposium on Industrial Electronics (ISIE)

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-Active charge balancing is an approved technique to implement high performance lithium-ion battery systems. Enhanced balancing speeds and reduced balancing losses are feasible compared to passive balancing. The new architecture proposed in this paper overcomes several drawbacks of other active balancing methods. It consists of only 2 non-isolated DC/DC converters. In combination with a MOSFET switch matrix it is able to balance arbitrary cells of a battery system at high currents. Adjacent cells can be balanced simultaneously. For the given setting, numerical simulations show an overall balancing efficiency of approx. 92.5%, compared to 89.4% for a stack-tocell-to-stack method (St2C2St, bidirectional fly-back) at similar balancing times. The usable capacity increases from 97.1% in a passively balanced system to 99.5% for the new method.

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An alternating direction method of multipliers algorithm for symmetric model predictive control

Danielson

2020

Optim Control Appl Methods

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SummaryThis article presents an alternating direction method of multipliers (ADMM) algorithm for solving large‐scale model predictive control (MPC) problems that are invariant under the symmetric‐group. Symmetry was used to find transformations of the inputs, states, and constraints of the MPC problem that decompose the dynamics and cost. We prove an important property of the symmetric decomposition for the symmetric‐group that allows us to efficiently transform between the original and decomposed symmetric domains. This allows us to solve different subproblems of a baseline ADMM algorithm in different domains where the computations are less expensive. This reduces the computational cost of each iteration from quadratic to linear in the number of repetitions in the system. In addition, we show that the memory complexity for our ADMM algorithm is also linear in number of repetitions in the system, rather than the typical quadratic complexity. We demonstrate our algorithm for two case studies; battery balancing and heating, ventilation, and air conditioning. In both case studies, the symmetric algorithm reduced the computation‐time from minutes to seconds and memory usage from tens of megabytes to tens or hundreds of kilobytes, allowing the previously nonviable MPCs to be implemented in real time on embedded computers with limited computational and memory resources.

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Performance evaluation of battery balancing hardware

Cited by 33 publications

References 18 publications

Simplified control for redistributive balancing systems using bidirectional flyback converters

Simplified control for redistributive balancing systems using bidirectional flyback converters

A Novel Non-Isolated Active Charge Balancing Architecture for Lithium-Ion Batteries

An alternating direction method of multipliers algorithm for symmetric model predictive control

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