Fuzzy Logic Energy Control technology

Author: Rointe

Take energy optimisation to the next level with Fuzzy Logic Energy Control. Discover how it maximises energy savings without reducing comfort here.

Take energy optimisation to the next level with ECO energy-saving technology.

All Rointe products include patented energy-saving technologies, developed exclusively by our electric heating experts, to increase your savings without reducing comfort. We call it Fuzzy Logic Energy Control.

Developed by us, Fuzzy Logic Energy Control improves the energy management required to maintain a stable temperature by accurately analysing thermal variations within ± 0.25ºC. Together with high purity aluminium and biodegradable thermal fluid, our low consumption technology transfers heat to the atmosphere in the most efficient way for your warmth and comfort.

Fuzzy Logic Energy Control works in 2 distinctive ways:

  • Energy optimisation

Fuzzy Logic Energy Control predicts the amount of energy required to reach the desired temperature. The energy demand is then proportionally reduced, smoothing the initial curve by lowering the peak temperature.

  • Temperature stabilisation

Once the desired temperature has been reached, the technology generates micro-cuts in the energy consumption to maintain a stable temperature, within a thermal variation of only ± 0.25ºC (compared to ± 2ºC in other competing systems).

Defined by Rointe, the equivalent coefficient consumption ratio is used to calculate the effective power (or average power of use) of our products based on their nominal power.



How is it obtained?

In an independent laboratory test carried out by BSRIA, one of our 1,430 W radiator with Optimizer Energy Plus technology was tested. This concluded that to maintain a room temperature of 21ºC with a variation of only ± 0.25ºC during a period of 24 hours, our radiator only needed an average of 572 W or 40% of its nominal power.

Improving energy efficiency with Fuzzy Logic Energy Control

We wanted to develop a newer technology that would improve energy efficiency even further, so we created Fuzzy Logic Energy Control. This improves the algorithm of our previous technology, Optimizer Energy Plus.

In a comparative test, carried out in a fair climatic chamber, we tested our latest low consumption technology (Fuzzy Logic Energy Control) against the previous one. This concluded that Fuzzy Logic Energy Control was able to save a further 6% of energy and reduce the equivalent coefficient of consumption to 38%, our best ever.