There are many points in the brewing process where the temperature is desired to remain constant or static. But what are the electronic methods for doing this, how did they do it, and what are their limitations.
Why do we want consistent temperature during the brewing process? Because several enzymes and micro-organisms work within specific temperate ranges.
For enzymes, too hot, and the enzymes are denatured (killed)—too cold and insufficient energy for the enzymes to complete the reaction. For the enzymes used in brewing during the mash, the working range across the enzymes is between 50°C(122°F) and 80°C (177°F). So, each enzyme has about a ~20°C (40°F) working range. See the graph below of the activity ranges for alpha and beta-amylase.
Figure 1 Lewis, M. J., & Young, T. W. (2002). Brewing Second Edition. New York, Boston, Dordrecht, London, Moscow: Kluwer Academic / Plenum Publishers.
From the graph above, if you have a mash temperature of 50-76°C (122-170°F) and enough time, you will create fermentable sugars from the starch in the grains for fermentation. I mentioned time before, and from the graph above, you can see that the maximum activity of the enzymes is ~62°C (143°F) and 70°C (158°F). This means these temperatures are when the enzymes convert starch into fermentable sugars at the fastest possible rate. This is important to brewers because we don’t want to wait around all day using energy for the conversion to finish. This is also why we crush the grain. They would convert as if they were uncrushed, but this would take a long time. Therefore, so brewers aren’t waiting around, all-day brewers will typically mash between 60-70°C (140-158°F) for maximum conversion rate.
Alpha and beta-amylase have slightly different functions when converting starch into fermentable sugars. Starch is effectively a long chain of glucose molecules. Alpha and beta-amylase break the bonds between the glucose molecules in the starch to release the fermentable sugars (glucose, maltose and maltotriose). Alpha-amylase breaks α-1,6 links in the chains, which creates more maltose and maltotriose, which are less fermentable by the yeast, and more residual sweetness in the finished beer. At the same time, Beta amylase breaks α-1,4 links which creates more glucose which is very fermentable by the yeast, and less residual sweetness in the finished beer. There is much more to it than this, but there are whole books about it.
So, in theory, by adjusting the temperature, you change the proportion of which enzyme is more active and, therefore, change the final residual sweetness. There have been many studies done on this, and essentially the result is inconclusive between all but the extreme temperature differences 64°C when a very high proportion of beta is an active and small amount of alpha and 74°C when there is a significant portion of alpha is active. A minimal amount of beta is active. But between 60-70°C, the results are 50/50 on whether the difference in temperature affects the final residual sweetness.
If we are brewing in that range and it only may make a difference to the final perceived sweetness, why control the temperature within this range? The answer is that if you want to make beer on the same equipment, then you don’t need to control the temp within this range. But the reason to control the temperature more precisely and accurately is to make the same beer more repeatable across different systems and scales, which is more critical when working in the commercial space.
During fermentation, the temperature is potentially more critical because compared to the mash, rather than relying on a chemical structure to complete a task, you depend on a living organism to complete the job, and we all know getting living organisms to do precisely what you want when you want it can be challenging.
There are hundreds of strains of brewer’s yeast out there, and depending on the strain, they will convert the wort into beer at a particular temperature range between 6-40°C (43-104°F). The breadth can be considered the range in temperature where the yeast will do its best work and usually spans 4-15°C (8-30°F). Like humans, if our working environment is too hot or too cold, our work will not be at its best, and this is the same for the yeast. As the temperature becomes colder, the yeast will become more sluggish as the yeast will be ‘sleepy’ and have insufficient energy to complete the chemical reaction (sugar to alcohol). When the temperature is warmer, the yeast becomes ‘lazy’, and there is so much energy that it is easy to produce a range of chemical reactions (not just the ones we want). Furthermore, as yeast cells are small and relatively simple in structure, even small temperature changes affect yeast significantly, so the general rule is that changes in temperature by greater than 30°C (60°F) in 24 hours are not recommended. If the maximum temperature change is recommended in 24 hours, then constant temperature fluctuations by 1/3 or more of the maximum can’t be good for the yeast.
Now that we have discussed when and why temperature control is important in the brewing process, we can talk about the thermal aspects of temperature control. In temperature-controlled systems, there are always two forces: the heating component and the cooling component resist each other. Both forces can be controlled electronically in some systems like a fermenter with a heating belt and a glycol chiller set-up. In many systems, only the heating or the cooling component is controlled – such as a brewing system where the heating element can be actively controlled, and there is no active cooling. However, that doesn’t mean there isn’t a cooling component. In a brewing system, the cooling component is heat loss to the surroundings.
These actively controlled heating/cooling components typically only have the function of ‘On’ applying an effect or ‘Off’ not applying an effect. The controller is the device that decides when the heating/cooling component receives a signal to be in the ‘On’ state. But to make this decision, the controller needs input data. In this case, it requires an electronic thermometer that can send its data to the controller. NTC (negative temperature coefficient) type temperature sensors are the most common thermometers used for this function. An NTC thermistor uses the electrical resistance properties of ceramic or metal composites to measure temperature. These sensors are accurate to 0.050°C (0.025°F).
Now that the controller has input data and a way to apply a heating/cooling effect, how does it decide? A set of rules must be created so the controller knows what to do based on the input data. The simplest version of this is a process called Hysteresis (or ‘on-off’) control. This uses a target temperature value and an allowable range of values on either side of the target temperature when no action will be taken. The controller then reads the input data, and if the values fall within the allowed range, then no action is taken (If the heater is on, it will stay on. If the heater is off, it will stay off). If the values are not within this range, then an action is taken. This is effectively a ‘live’ system that reacts based on the data point received and is not influenced by any previous data.
Let's take an example system with hysteresis control with a target temperature of 200°C (680°F) and an allowable range of ±10C (20°F). This means that if the input temperature from the temperature probe is anywhere between 19-21°C (66-70°F), then the controller will not change the status of the heat/cooling output. If the temperature is outside the range, then an action is taken (change the heating or cooling status). The good thing about hysteresis control is that the coding to make it work is relatively simple, and the components are inexpensive.
This system works. But it’s not very stable, as there are constant swings within the temperature range. There is also always a delay in the system between the thermal action (the heating or cooling) changing the temperature of the substance it is heating/cooling, which is registered by the temperature probe and feeding back to the controller (this is called the lag). This problem is when the system is controlled only by the current temperature reading. This is further influenced by any residual heating or cooling capacity from the heating/cooling component, meaning these systems can be susceptible to overshoot and undershoot of the target temperature and the minimum and max of the temperature range.
Programmers can try to improve this simple hysteresis temperature control by adding features like a timer to periodically turn on and then off the heating/ cooling when the temperature they are controlling is within the allowable range. If the switching timing is correct, this can help stabilise the temperature closer to the target temperature. The main issue with this method is that frequent switching will reduce the lifespan of the relays in the controller, so this limits the practical usage of this method.
Another method that can be used to reduce temperature fluctuations in a hysteresis system is to reduce the heating power input. Some brewing systems have dual heating element switches to achieve this, which allows a lower power setting to be used during the mash. This can reduce fluctuations, but depending on the brewing and environmental conditions, it can also result in a lower average temperature.
How can more precise and stable temperature control be achieved? One commonly used control method is a PID controller. PID control systems use temperature data collected over a period of time to calculate an appropriate heating input percentage and optimise performance. The calculation of the required heating input is split into three aspects, each described below:
The P (Proportional) component uses temperature data at a single point in time. This aspect of the calculation is based on the difference between the measured temperature and the set temperature. When the measured temperature approaches the set temperature, this difference approaches zero; therefore, the calculated heating input also approaches zero. Since some heating power is required to maintain elevated temperatures, purely proportional controllers have a ‘steady-state error’, which means the temperature tends to sit below the set point once stabilised.
The I (Integral) component uses temperature history data to reduce the steady-state error. When the system spends time below the set-point, this history builds up and is used to increase the calculated heat input required.
The D (Derivative) component uses the current slope/trend of the temperature data. This allows the system to detect rapid changes in temperature and adjust heating input to prevent overshoots/undershoots. One example is when the G40/G70 moves from strike temperature to the first mash step – the set temperature decreases, and grain is added. Since the measured temperature drops quite quickly, the derivative component kicks in, and the controller applies some heating to reduce undershoot.
The control system combines the above 3 PID components to calculate the appropriate heating percentage. In Grainfather PID controllers, this heating input percentage is achieved by quickly pulsing the heater on and off using hardware capable of rapid switching.
The development and tuning of PID systems are complex and highly technical. In brewing systems, this is further complicated by accommodating various batch volumes, grain weights, water to grist ratios etc. The Grainfather development team focus on designing systems that get up to temperature quickly, don’t overshoot too much and maintain a stable temperature – all while finding a balance for optimising performance across various brewing scenarios. An example of typical results from our PID controllers is shown in the G40 plot below.
In summary, hysteresis control is suitable for achieving basic temperature control in simpler brewing systems. PID control provides much better performance and repeatability, but the hardware is more expensive, and software development is much more involved.
Works Cited
Exeter, U. o. (n.d.). Types of Feedback Control. Retrieved from University of Exeter: https://newton.ex.ac.uk/teaching/CDHW/Feedback/ControlTypes.html
Fix, G. (1999). Principles of Brewing Science 2nd Ed. Brewers Publications.
Lewis, M. J., & Young, T. W. (2002). Brewing Second Edition. New York, Boston, Dordrecht, London, Moscow: Kluwer Academic / Plenum Publishers.
Palmer, J. J. (2017). How to Brew 4th Edition. Boulder: Kristi Switzer.
VANCE VANDOREN, P. (2016, July 16). Understanding PID control and loop tuning fundamentals. Retrieved from Control Engineering: https://www.controleng.com/articles/understanding-pid-control-and-loop-tuning-fundamentals/