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Oversizing the battery pack is simple, but also comes with an increase in weight, volume and cost. Screening and selection of cells is time and therefore cost intensive, and it is not easy to identify at the beginning-of-life what will be the limiting cell in the future.
Furthermore, the performance will still be limited by the weakest cell in both cases. Parallelization adds redundancy and averages the electrical performance, and it does so without additional losses, unlike electronic solutions. However, it complicates cell integration and management, and creates the problem of uneven cell currents, which may reduce useful life.
Passive balancing systems enable selective discharge of higher capacity cells into a resistor during charging, allowing all cells to be fully charged at the end-of-charge. Thus, losses in useful capacity related to differences in initial state-of-charge (SOC) are compensated for.
However, there are still the problems of SOC imbalance during discharge, power imbalance, uneven temperatures, wasted energy and thermal management of the balancing resistors, which limits the max. balancing currents.
Active balancing systems have also been proposed, but the automotive industry usually considers their advantages insufficient to justify their extra cost and complexity. Using power electronics, they conduct selective charge or discharge of cells during all modes of operation, allowing all cells to be always at a similar SOC. Thus, losses in useful capacity related to differences in SOC are minimized and charging times are shortened. However, the problems of power imbalance or uneven temperature distributions still remain.
Recently, a new generation of active balancing systems that offer more control features have been proposed. The concept of simultaneous SOC and thermal balancing was introduced by Altaf [1] [2] [3], being applied to a cascaded multi-level converter used at the same time as an integrated cell balancer and motor driver in an e-mobility application.
Barreras and Pinto [4] – [8] extended these studies, considering non-integrated approaches, improving the simulation models of the battery and the power electronics, re-formulating the optimal problem and developing a proof-of-concept prototype.
Additional control objectives were proposed, like minimization of losses, equalization of power capability or maximization of useful capacity. Such active balancing systems with multiple control goals and, typically, higher current capability, were called smart balancing systems (SBS) [7].
From the simulation-based analysis of hundreds of e-mobility scenarios [5] [6], it was concluded that the performance benefits of integration of a SBS in a battery pack depend strongly on a number of factors. In general, better results were obtained for: SBSs with bidirectional energy transfer and higher efficiency; smaller battery pack sizes; battery packs with higher cell-to-cell differences; vehicles with more demanding driving cycles; worse heating/cooling conditions; and a wider SOC operating window.
A proof-of-concept prototype of a SBS was presented in [8], using dual half bridge converters to transfer energy from the cells of the battery pack to a supercapacitor bank and vice versa. Such a distributed hybridization topology enabled further minimization of losses and maximization of power capability. In this case, the optimal control approach proposed was offline and required knowing all the inputs in advance, which means that the battery pack power profile was known in advance.
From all the results presented in [1] – [8] it can be concluded that, under certain scenarios, the SBS can overcome not some, but all the problems related with cell-to-cell variations, making the battery pack virtually ideal, with the disadvantage of some losses in the power electronics. The SBS can transfer the energy between cells in such a way that the temperatures are minimized and equalized, and the electrical performance is optimized, in terms of losses, power capability and useful capacity during all modes of operation.
More research is needed to effectively evaluate the impact of the SBS on the battery pack useful life and evolution of the cell-to-cell variations over time.
In addition, new optimal control approaches suitable for online implementation are also required. There are trade-offs between conflicting objectives of a SBS. For example, in order to equalize power capability or maximize useful capacity, a certain SOC imbalance may be required.
However, this may promote uneven cell aging. Another example: the temperature operating window can be made narrower in exchange for higher balancing losses. All this makes the development and tuning of online control approaches for SBS not trivial, not to mention the well-known challenges posed by diagnosis and prognosis algorithms, which must also be taken into account.
SBS could also leverage the advantages of so called smart cells to further optimize the performance of battery packs. A battery system made of smart cells utilizes power electronics between each cell (or group of cells) and the battery bus bar.
This removes the requirement of a separate balancing power bus and enables designs with high modularity, flexibility, decentralization, balancing current capability, and ability to isolate faulty cells, but once again at the expense of extra cost and complexity. Frost [9] and Máthé [10] presented different modular multi-level converter topologies in this context, proposing either equalization algorithms for terminal voltage [9] or SOC [10].
References
[1] F. Altaf, L. Johannesson and B. Egardt, "Simultaneous Thermal and State-of-Charge Balancing of Batteries: A Review," 2014 IEEE Vehicle Power and Propulsion Conference (VPPC), Coimbra, 2014.
[2] F. Altaf; B. Egardt; L. Johannesson, "Load Management of Modular Battery Using Model Predictive Control: Thermal and State-of-Charge Balancing," IEEE Transactions on Control Systems Technology, 2016.
[3] F. Altaf; B. Egardt, "Comparative Analysis of Unipolar and Bipolar Control of Modular Battery for Thermal and State-of-Charge Balancing," IEEE Transactions on Vehicular Technology, 2016.
[4] J. V. Barreras, C. Pinto, R. de Castro, E. Schaltz, S. J. Andreasen and R. E. Araujo, "Multi-Objective Control of Balancing Systems for Li-Ion Battery Packs: A Paradigm Shift?," 2014 IEEE Vehicle Power and Propulsion Conference (VPPC), Coimbra, 2014, pp. 1-7.
[5] C. Pinto; J. V. Barreras; E. Schaltz; R. Araujo, "Evaluation of Advanced Control for Li-ion Battery Balancing Systems using Convex Optimization," in IEEE Transactions on Sustainable Energy, vol. 7, no. 4, pp. 1703-1717, Oct. 2016.
[6] J. V. Barreras, “Practical Methods in Li-ion Batteries: for simplified modeling, battery electric vehicle design, battery management system testing and balancing system control,” PhD. Dissertation, University of Aalborg, 2017.
[7] J. V. Barreras, D. A. Howey, “Smart balancing systems: towards virtually ideal Li-ion battery packs,”3rd International Conference and Exhibition on Automobile Engineering, Berlin, 2017.
[8] C. Pinto, “Sizing and Energy Management of a Distributed Hybrid Energy Storage System for Electric Vehicles,” PhD. Dissertation, University of Porto, 2018.
[9] D. F. Frost, D. A. Howey, “Completely Decentralized Active Balancing Battery Management System,” in IEEE Transactions on Power Electronics, vol. 33 no. 1, pp. 729-738, Jan. 2018.
[10] L. Mathe, E. Schaltz and R. Teodorescu, "State of charge balancing after hot swap for cascaded H-bridge multilevel converters," 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), Brasov, 2017, pp. 741-746. | 
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