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Safely and efficiently managing a battery pack consisting of hundreds to thousands of battery cells is a critical but challenging task due to commonly observed uncertainties, e.g. temperature, battery degradation and SOC estimation inaccuracy. This paper proposes a robust and efficient most significant cell methodology that estimates the battery pack SOC depending on the determined most significant cells. The estimation adopting this methodology is robust to variations of temperature, battery degradation and battery cell SOC estimation inaccuracy. A battery pack simulator and a real battery pack designed for electric vehicles were used as prototypes to illustrate the high performance, robustness and effectiveness of the proposed methodology. Moreover, the proposed algorithm requires light computational effort, making it suitable for real-time operation.

We propose a dual decomposition based algorithm that solves the AC optimal power flow (ACOPF) problem in the radial distribution systems and microgrids in a collaborative and distributed manner. The proposed algorithm adopts the sec-ond-order cone program (SOCP) relaxed branch flow ACOPF model. In the proposed algorithm, bus-level agents collaboratively solve the global ACOPF problem by iteratively sharing partial variables with its 1-hop neighbors as well as carrying out local scalar computations that are derived using augmented Lagrangian and primal-dual subgradient methods. We also propose two distributed computing platforms, i. e., high-perfor-mance computing (HPC) based platform and hardware-in-the-loop (HIL) testbed, to validate and evaluate the proposed algorithm. The computation and communication performances of the proposed algorithm are quantified and analyzed on typical IEEE test systems. Experimental results indicate that the proposed algorithm can be executed on a fully distributed computing structure and yields accurate ACOPF solution. Besides, the proposed algorithm has a low communication overhead.

Batteries as a multi-disciplinary field have been analyzed from the electrical, material science and electrochemical engineering perspectives. The first principle-based four-dimensional degradation model (4DM) of the battery is used in the article to connect the interdisciplinary sciences that deal with batteries. The 4DM is utilized to identify the physical manifestation that electrolyte degradation has on the battery and the response observed in the terminal voltage. This paper relates the different kinds of side reactions in the electrolyte and the material properties affected due to these side reactions. It goes on to explain the impact the material property changes has on the electrochemical reactions in the battery. This paper discusses how these electrochemical reactions affect the voltage across the terminals of the battery. We determine the relationship the change in the terminal voltage has due to the change in the design properties of the electrolyte. We also determine the impact the changes in the electrolyte material property have on the terminal voltage. In this paper, the lithium ion concentration and the transference number of the electrolyte are analyzed and the impact of their degradation is studied.