Automatic controller tuning for soft sensor based flow rate control

Leonow, Sebastian; Mönnigmann, Martin

doi:10.3182/20140824-6-za-1003.02356

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…The SS is based on data measured by a smart meter installed in the Low Voltage substation. Leonow and Mönnigmann (2014) replaced an expensive flowmeter used in low-speed radial pumps with a SS to calculate the flow in real-time. Moreover, Järvisalo et al (2016) developed an SS, based on real-time monitoring of the specific energy consumption, to save electricity in air compressors.…”

Section: Soft Sensorsmentioning

confidence: 99%

Energy management in the formation of light, starter, and ignition lead-acid batteries

et al. 2018

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This paper discusses energy management in the formation process of lead acid batteries. Battery production and electricity consumption in during battery formation in a battery plant was analyzed over a 4 year period. The main parameters affecting the energy performance of battery production were identified and different actions to improve it were proposed. Furthermore, an Energy Performance Indicator (EnPI), based on the electricity consumption of battery formation (a difficult and rather expensive parameter to measure), is introduced to assess its energy efficiency. Therefore, a Soft Sensor to measure the electricity consumption in real-time (based on the voltage and current measured during battery formation), and to calculate the EnPI is developed. Moreover, Energy Management (EM), aided by the use of energy baselines and control charts is implemented to assess the energy performance of battery formation, allowing the implementation of rapid corrective actions toward higher efficiency standards. This resulted on the average in a 4.3% reduction of the electricity consumption in battery formation.

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Section: Soft Sensorsmentioning

confidence: 99%