Study on the resistivity behaviour of graphite-based resistors used in sol-gel thick film heaters
Study on the resistivity behaviour of graphite-based resistors used in sol-gel thick film heaters
批准号:
549184-2019
负责人:
Mowat, Vicki
金额:
$1.82万
依托单位国家:
加拿大
项目类别:
Applied Research and Development Grants - Level 1
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31
中文摘要
Datec Coating Corporation是一家加拿大的定制加热元件和高性能涂层制造商,主要基于专利和专有的溶胶凝胶技术。 该公司由皇后大学的2 PhD科学家于20世纪90年代中期创立,并已发展成为厚膜加热技术的领导者,涵盖汽车(电动汽车电池加热器),医疗设备和电子产品等各个领域。 两个产品平台涉及使用Datec的溶胶-凝胶化学方法制造的石墨基电阻器。 一种利用云母作为加热器基板,另一种利用铝基板。 尽管石墨基加热器相对于现有技术具有显著的竞争优势,但在某些情况下,石墨加热器的电阻率已经被观察到以不可预测的方式显著漂移,这取决于应用变量(功率密度、温度、相对湿度、电压、电流密度、占空比)以及设备的历史。 云母加热器的电阻漂移行为不同于铝加热器。该项目的第一个目标是设计和执行实验,以确定和系统地评估控制电阻漂移的变量,以便进行预测建模。 由于该现象的复杂性和影响电阻率漂移的众多因素,预计将在Datec的研发能力的支持下开发人工神经网络模型。 此外,将按照科学方法设计和执行实验,以检验有关电阻率漂移机制的假设。 这项工作的结果将为下一代电阻器设计提供信息,这是Datec的核心技术。
英文摘要
Datec Coating Corporation is a Canadian manufacturer of custom heating elements and high-performancecoatings based primarily on patented and proprietary sol gel technologies. The company was founded by 2PhD scientists from Queen's University in the mid 1990's and has since grown into a leader in thick filmheating technology over various segments including automotive (electric vehicle battery heaters), medicaldevices and electronics. Two product platforms involve graphite-based resistors created using Datec's sol-gel chemistry. One utilizes mica as the heater substrate and the other utilizes aluminum substrate. Although the graphite-based heater has significant competitive advantages over the state of the art, the resistivity of thegraphite heater has been observed in some instances to drift significantly and in an unpredictable way, depending on application variables (power density, temperature, relative humidity, voltage, current density,duty cycle) as well as on the history of the device. The resistance drift behaviour is different for mica heaters than aluminum heaters. The first objective of the project is to design and execute experiments to identify and systematically evaluate the variables governing resistance drift for the purpose of predictive modelling. Due tothe complexity of the phenomenon and the apparently numerous factors affecting resistivity drift, it isenvisioned that an artificial neural network model will be developed with the support of the R&D capability at Datec. Additionally, experiments will be designed and executed following scientific method to test hypothesesregarding the mechanisms governing resistivity drift. The results of this work will inform the next generation of resistor design, which represents core technology to Datec.
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