Energy efficient battery management

Chiasserini, Carla-Fabiana; Rao, Ramesh R.

doi:10.1109/49.932692

Cited by 224 publications

(85 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[89], [90], [92] - [97] MT Multiple batteries It employs the recovery effect of batteries. [98] order adaptation, and power control for MTs. In a distributed mechanism, given a subcarrier assignment, an MT adjusts its modulation order and transmission power to optimize its own energy efficiency.…”

Section: Multiple Retailersmentioning

confidence: 99%

A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

Ismail

Zhuang

Serpedin

et al. 2015

IEEE Commun. Surv. Tutorials

143

View full text Add to dashboard Cite

Efficient usage of energy in wireless networks represents a major concern in academia and industry, mainly because of environmental, financial, and quality-of-experience considerations. Various solutions have been proposed to enable efficient energy usage in wireless networks, and these approaches are referred to as green wireless communications and networking. In this survey, we mainly focus on energy efficient techniques in base stations and mobile terminals as they constitute the major sources of energy consumption in wireless access networks, from the operator and user perspectives, respectively. Unlike the existing articles and surveys, we aim to present a unified treatment of green solutions and analytical models for both network operators and mobile users. Such a unified treatment will help in the future to develop green solutions that enable an improved and balanced efficient usage of energy by operators and end users. Dr Qaraqe has held a variety positions in many companies and he has over 12 years of experience in the telecommunication industry. Dr Qaraqe has worked for Qualcomm, Enad Design Systems, Cadence Design Systems/Tality Corporation, STC, SBC and Ericsson. He has worked on numerous GSM, CDMA, WCDMA projects and has experience in product development, design, deployments, testing and integration. Dr Qaraqe joined the department of Electrical and Computer Engineering of Texas A&M University at Qatar, in July 2004, where he is now a professor. Dr Qaraqe research interests include communication theory and its application to design and performance, analysis of cellular systems and indoor communication systems. Particular interests are in mobile networks, broadband wireless access, cooperative networks, cognitive radio, diversity techniques and beyond 4G systems.

show abstract

Section: Multiple Retailersmentioning

confidence: 99%

A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

Ismail

Zhuang

Serpedin

et al. 2015

IEEE Commun. Surv. Tutorials

143

View full text Add to dashboard Cite

show abstract

“…In addition, the model was used to investigate effects of material properties on performance, which include transference number [5], activity coefficient in electrolyte [6], diffusion coefficient in LiPF 6 electrolyte [7], and particle size distributions on the discharge capacity [8]. Furthermore, the model was improved by adding the energy equation [9] and the efficiency of batteries during cycling was investigated [10]. Effects of side reactions were also studied [11].…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and analysis of a pouch type LiMn2O4/Carbon high power Li-polymer battery based on electrochemical-thermal principles

Xiao

Choe

2012

Journal of Power Sources

View full text Add to dashboard Cite

“…16,25,26 The extended Kalman filter also directly provides an estimate of error of the state, 16 though inaccuracy in the cell model used can lead to overconfidence in the state estimates. 26 Chiasserini and Rao 30 presented a stochastic battery model that closely matched results obtained through an electrochemical model and used the stochastic model to explore battery management techniques that improve the battery capacity. Their simulation shows that a battery is able to deliver the maximum available capacity at the cost of a fairly small additional delay and complexity.…”

mentioning

confidence: 97%

Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation

Northrop

Suthar

Ramadesigan

et al. 2014

J. Electrochem. Soc.

View full text Add to dashboard Cite

Improving the efficiency and utilization of battery systems can increase the viability and cost-effectiveness of existing technologies for electric vehicles (EVs). Developing smarter battery management systems and advanced sensing technologies can circumvent problems arising due to capacity fade and safety concerns. This paper describes how efficient simulation techniques and improved algorithms can alleviate some of these problems to help electrify the transportation industry by improving the range of variables that are predictable and controllable in a battery in real-time within an electric vehicle. The use of battery models in a battery management system (BMS) is reviewed. The effect of different simulation techniques on computational cost and accuracy are also compared, and the validity of implementation in a microcontroller environment for model predictive control (MPC) is addressed. Using mathematical techniques to add more physics without losing efficiency is also discussed. Behavioral predictions can be made using mathematical models without the need to directly observe the states using expensive and time consuming physical experiments. Such predictions allow for more intelligent design of new systems, which is generally limited by the mathematical techniques used and the computational resources available. An improved modeling and simulation approach can achieve the following goals when applied to engineering systems: r More accurate predictions by using more meaningful models r Faster simulation with fewer computational resources r Optimization of design parameters r Better control, allowing aggressive performance while maintaining safetyHere we focus on the application of such principles to the use of physics-based battery models in battery management systems in electric vehicles.In recent years, battery electric vehicles (BEV) have increased in popularity to reduce the dependence on fossil fuels. Lithium-ion batteries are a popular choice as an energy storage medium for high demand applications due to their large energy density but are not utilized to their full capacity in BEV applications; operating a Li-ion battery too aggressively can lead to reduced cycle life and unpredictable thermal runaway reactions. These challenges reduce the functional capacity of the battery available for propulsion.The consumer expects the vehicle's performance and capabilities to remain uniform regardless of the state of charge or age of the battery, as they have become accustomed to internal combustion engines. When the battery is nearly depleted, it is difficult or impossible to satisfy high power demand, which is aggravated as the battery ages. To avoid these difficulties, the BMS shuts off the battery with a large amount of energy unused, so that Li-ion batteries for EVs are greatly overdesigned and carry extra weight and volume, reducing efficiency and increasing cost.1 Research is underway to better understand the internal limitations of Li-ion batteries including SEI layer growth, side * Electrochemical Society ...

show abstract

Energy efficient battery management

Cited by 224 publications

References 17 publications

A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

Dynamic modeling and analysis of a pouch type LiMn2O4/Carbon high power Li-polymer battery based on electrochemical-thermal principles

Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation

Contact Info

Product

Resources

About