This paper describes a thermal model that represents the heat generation behavior of a large format (10.5 Ah) Li-ion pouch cell. The thermal model is based on the calculation of the heat generation from experimental measurements of internal resistance and the entropic heat coefficient. Predictions from the thermal model are compared with experimental adiabatic calorimetry data. Higher discharge rates and larger temperature operation ranges than the ones reported in prior studies are considered. Results from the thermal model simulations have a prediction error of 21% in comparison with the experimental ones for discharge processes carried out at moderate rates. For discharge processes carried out at high discharge rates a maximum prediction error of 15% has been determined. The advantages and disadvantages of the model are further discussed, taking into account aspects such as accuracy, model development and implementation in different thermal management system designs.The rechargeable battery industry will experience significant growth in the near future given the increased need for battery systems for power electronics, renewable energy storage and power systems for transportation applications. 1 These new applications require large format lithium-ion (Li-ion) cells (2-100 Ah) that need to be integrated in large scale modules and packs and be managed by ad hoc control electronics, the so-called battery management systems (BMS). 2 New large format Li-ion batteries are rapidly becoming available from commercial cell manufacturers. 3,4 However, these cells still have many problems that need to be overcome -problems such as operating temperature behavior and cell temperature non-uniformities, 5 among others -which could result in accelerated degradation of the battery power performance and the reduction of the operating life, 6 critically affecting the safety issues of battery packs.Therefore, the kinds of applications that are powered by largescale Li-ion batteries make it necessary to design thermal management systems (TMS) that improve battery performance. A precise determination of heat generation in batteries could improve the TMS design process. Several investigations deal with the thermal modeling of single-cell batteries 7-11 and battery packs. 12-14 Some of these models predict heat generation rates based on experimental data 5,12,15-19 or electrochemical models. 8,10,13,14,[20][21][22] Pals and Newman 10,14 developed a thermal model for a Li-ion cell based on the electrochemical model presented by Doyle et al. 23 Song and Evans 13 took a similar approach and presented a 2D thermal model for a cell stack where the heat generation was estimated from a 1D electrochemical model. Such models are well-suited for designing batteries, but they are not suitable for the computational resources of the electronics used in BMSs. 24 Experimental studies show that the overpotential and entropic heat coefficients gathered from experiments can be used to predict the volumetric heat generation rate. These thermal simulat...
Battery lifetime prognosis is a key requirement for successful market introduction of rechargeable EnergyStorage Systems (ESS) based on lithium-ion (Li-ion) technology. In order to make decisions at the system design stage, a procedure for making efficient predictions of battery performance over time is necessary to be developed.In this paper, a general methodology for the evaluation of lifetime prediction is presented, covering the semi-empirical aging model precision and validity. Both calendar-life and cycle-life performance were investigated. Moreover, standing time and working operation were examined jointly using realistic operating profiles. The aim was the predictive model to be suitable for any application, including electric vehicle (EV), within the considered operating range. The efforts were especially focused on model ratification procedures and predictions goodness evaluation. The validation processes not only dealt with static impact factors evaluation but also with dynamic operation schemes. Besides, integration of ageing monitoring algorithm into Battery Management System (BMS) was evaluated. Battery pack design and operation strategies definition criteria were also discussed based on the stress factors influence on cell performance. The presented results correspond to a lithium iron phosphate (LFP) cathode 26650-size Li-ion cell.
Combustion control requires visible photodetectors to sense the CH* CL emission at 430 nm that combined with a visible-blind UV photodetector allows us to obtain the OH*/CH* ratio. UV-visible P-InGaN/GaN multiple quantum well-N photodiodes with 15-18 mm2 areas were fabricated to conduct OH* (308 nm) and CH* CL detection without external filters. Bandpass detectors at 230-390 nm and 360-450 nm presented linear responses over five decades and rejection ratios >10(3) at 430 and 308 nm, respectively. A full optical sensor system was built and detectors operated at 120 degrees C in a combustion chamber, showing linear responses within the dynamic range, maximum signal-to-noise ratios of 103 and response times of <1 s. An exponential association dependence between the optical OH*/CH* CL signals and the gas/air ratios was found.
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