Experimental and analytical study on heat generation characteristics of a lithium-ion power battery

This document is the Accepted Manuscript version of the following article: Yongqi Xie, Shang Shi, Jincheng Tang, Hongwei Wu, and Jianzu Yu, ‘Experimental and analytical study on heat generation characteristics of a lithium-ion power battery’, International Journal of Heat and Mass Transfer, Vol. 122: 884-894, July 2018. Under embargo until 20 February 2019. The final, definitive version is available online via: https://doi.org/10.1016/j.ijheatmasstransfer.2018.02.038A combined experimental and analytical study has been performed to investigate the transient heat generation characteristics of a lithium-ion power battery in the present work. Experimental apparatus is newly built and the investigations on the charge/discharge characteristics and temperature rise behavior are carried out at ambient temperatures of 28 °C, 35 °C and 42 °C over the period of 1 C, 2 C, 3 C and 4 C rates. The thermal conductivity of a single battery cell is experimentally measured to be 5.22 W/(m K). A new transient model of heat generation rate based on the battery air cooling system is proposed. Comparison of the battery temperature between simulated results and experimental data is performed and good agreement is achieved. The impacts of the ambient temperature and charge/discharge rate on the heat generation rate are further analyzed. It is found that both ambient temperature and charge/discharge rate have significant influences on the voltage change and temperature rise as well as the heat generation rate. During charge/discharge process, the higher the current rate, the higher the heat generation rate. The effect of the ambient temperature on the heat generation demonstrates a remarkable difference at different charge states.Peer reviewe

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Development of optimum Mariner spacecraft power system for application to future flyby and orbiter mission

Data Cache-Energy and Throughput Models: Design Exploration for Embedded Processors

Most modern 16-bit and 32-bit embedded processors contain cache memories to further increase instruction throughput of the device. Embedded processors that contain cache memories open an opportunity for the low-power research community to model the impact of cache energy consumption and throughput gains. For optimal cache memory configuration mathematical models have been proposed in the past. Most of these models are complex enough to be adapted for modern applications like run-time cache reconfiguration. This paper improves and validates previously proposed energy and throughput models for a data cache, which could be used for overhead analysis for various cache types with relatively small amount of inputs. These models analyze the energy and throughput of a data cache on an application basis, thus providing the hardware and software designer with the feedback vital to tune the cache or application for a given energy budget. The models are suitable for use at design time in the cache optimization process for embedded processors considering time and energy overhead or could be employed at runtime for reconfigurable architectures

Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER

A Real-Time evaluation system for a state-of-charge indication algorithm

The known methods of State-of-Charge (SoC) indication in portable applications are not accurate enough under all practical conditions. This paper describes a real- time evaluation LabVIEW system for an SoC algorithm, that calculates the SoC in [%] and also the remaining run-time available under the valid discharge conditions. With the described system the accuracy of the SoC algorithm and its validity can be determined. The final goal of the SoC algorithm is to predict the remaining capacity of the battery and the remaining run-time with an accuracy of 1 minute or better under all realistic user conditions, including a wide variety of load currents and a wide temperature range. The basis of the SoC algorithm is current measurement and integration during charge and discharge state and voltage measurement during equilibrium state. Experimental results show the testing ability of the real-time evaluation system and the effectiveness of the novel approach for improving the accuracy of the SoC indication

Powering a Biosensor Using Wearable Thermoelectric Technology

Wearable medical devices such as insulin pumps, glucose monitors, hearing aids, and electrocardiograms provide necessary medical aid and monitoring to millions of users worldwide. These battery powered devices require battery replacement and frequent charging that reduces the freedom and peace of mind of users. Additionally, the significant portion of the world without access to electricity is unable to use these medical devices as they have no means to power them constantly. Wearable thermoelectric power generation aims to charge these medical device batteries without a need for grid power. Our team has developing a wristband prototype that uses body heat, ambient air, and heat sinks to create a temperature difference across thermoelectric modules thus generating ultra-low voltage electrical power. A boost converter is implemented to boost this voltage to the level required by medical device batteries. Our goal was to use this generated power to charge medical device batteries off-the-grid, increasing medical device user freedom and allowing medical device access to those without electricity. We successfully constructed a wearable prototype that generates the voltage required by an electrocardiogram battery; however, further thermoelectric module and heat dissipation optimization is necessary to generate sufficient current to charge the battery

GaAs monolithic RF modules for SARSAT distress beacons

Monolithic GaAs UHF components for use in SARSAT Emergency Distress beacons are under development by Microwave Monolithics, Inc., Simi Valley, CA. The components include a bi-phase modulator, driver amplifier, and a 5 watt power amplifier

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

Wireless sensors and IoT platform for intelligent HVAC control

Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.QREN SIDT [38798]; Portuguese Foundation for Science & Technology, through IDMEC, under LAETA [ID/EMS/50022/2013