Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)

Man, Ka Lok; Ting, T. O.; Krilavičius, Tomas; Wan, Kaiyu; Chen, C.; Chang, Jingbo; Poon, Sheung-Hung

doi:10.1109/bcfic.2012.6217989

Cited by 16 publications

(10 citation statements)

References 25 publications

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“…15) and can be used to prevent damage, ensure safety, and minimize charging time. 16 The SOH index measures the ability of the battery to store and deliver electrical energy; similar to the SOC, estimation-based approaches are used to predict the value of the SOH (e.g., see . The SOH tracks the long-term changes in a battery and its knowledge can help ABMS to anticipate problems through online fault diagnosis while providing charging profiles to slow down the battery aging.…”

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LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control

Torchio

Magni

Gopaluni

et al. 2016

J. Electrochem. Soc.

236

171

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Consumer electronics, wearable and personal health devices, power networks, microgrids, and hybrid electric vehicles (HEVs) are some of the many applications of lithium-ion batteries. Their optimal design and management are important for safe and profitable operations. The use of accurate mathematical models can help in achieving the best performance. This article provides a detailed description of a finite volume method (FVM) for a pseudo-two-dimensional (P2D) Li-ion battery model suitable for the development of model-based advanced battery management systems. The objectives of this work are to provide: (i) a detailed description of the model formulation, (ii) a parametrizable Matlab framework for battery design, simulation, and control of Li-ion cells or battery packs, (iii) a validation of the proposed numerical implementation with respect to the COMSOL MultiPhysics commercial software and the Newman's DUALFOIL code, and (iv) some demonstrative simulations involving thermal dynamics, a hybrid charge-discharge cycle emulating the throttle of an HEV, a model predictive control of state of charge, and a battery pack simulation. The increasing demand for portable devices (e.g., smartphones) and hybrid electric vehicles (HEVs) calls for the design and management of storage devices of high power density and reduced size and weight. During the many decades of research, different chemistries of batteries have been developed, such as Nickel Cadmium (NiCd), Nickel Metal Hydride (NiMH), Lead Acid and Lithium ion (Li-ion) and Lithium ion Polymer (Li-Poly) (e.g., see Refs. 1-4). Among electrochemical accumulators, Li-ion batteries provide one of the best tradeoff in terms of power density, low weight, cell voltage, and low self-discharge. 5 Mathematical models can support the design of new batteries as well as the development of new advanced battery management systems (ABMS). [6][7][8] According to the literature, mathematical models for Li-ion battery dynamics fall within two main categories: Equivalent Circuit Models (ECMs) and Electrochemical Models (EMs). ECMs use only electrical components to model the dynamic behavior of the battery. ECMs include (i) the R int model where only a resistance and a voltage source are used to model the battery, (ii) the RC model (introduced by the company SAFT 9 ) where capacitor dynamics have been added to the R int model, 10 and (iii) the Thevenin model, which is an extension of the RC model (e.g., see Refs. 11, 12 and references therein). In contrast, EMs explicitly represent the chemical processes that take place in the battery. While ECMs have the advantage of simplicity, EMs are more accurate due to their ability to describe detailed physical phenomena. 13 The most widely used EM in the literature is the porous electrode theory-based pseudo-two-dimensional (P2D) model, 14 which is described by a set of tightly coupled and highly nonlinear partial differential-algebraic equations (PDAEs). In order to exploit the model for simulation and design purposes, the set of PDAEs are reformu...

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LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control

Torchio

Magni

Gopaluni

et al. 2016

J. Electrochem. Soc.

236

171

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“…Also, systems such as Tesla Autopilot, requiring the download of 500 MB per update [7-10], and other Internet-connected Advanced Driver Assistance Systems perform continuous data collection from vehicles on the road (∼5.6 Gbps), aggregate them centrally, and share learnings back with the vehicles again. Moreover, these connected vehicles perform numerous data exchanges with cloud-hosted services, e.g., for over-the-air firmware updates, such as BMW [11], to support Connected Battery Management Systems [12], for 3D map updates [13,14], and for various AI-based driving functions.…”

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confidence: 99%

Revisiting WiFi offloading in the wild for V2I applications

et al. 2022

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This paper revisits the opportunities of using WiFi offloading for Vehicle to Internet (V2I) communication, and how this has changed over the last decade. With the rollouts of provider-managed WiFi networks that are more structured and operate under authenticated regimes, WiFi offloading, or use of available (roadside) WiFi networks for V2I data communication, has different opportunities and challenges. To study the current landscape,we develop a system (X-Fi), which efficiently selects, associates to, authenticates with, and performs WiFi offloading for V2I communication with these networks, and a tool (X-Perf ), which illustrates opportunities of WiFi offloading available today in these networks, with measurements and experiments across four metro areas across three continents over 22 months. Our results indicate the feasibility of achieving 1 GB/hour application goodput, an order of magnitude higher than the number provided by open WiFi networks in the past, which can take a significant load away from alternative communication paths for V2I systems. Moreover, we provide several implications on transport protocols and WiFi deployments to shed light on the use of such WiFi networks for V2I communication.

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“…Dans ce cas, elle doit être déconnectée du reste de la structure. Un superviseur -le Système de Management des Batteries ou BMS (Batteries Management System -s'emploie à ces opérations de surveillance du SoC [10] et du pilotage de l'équilibrage [11]. « Pour garantir une bonne durée de vie du système, le BMS doit en premier lieu pouvoir surveiller les grandeurs qui sont préjudiciables aux cellules qui composent la batterie.…”

Section: -Modélisationunclassified