Efficiency improvement in liquid-coupled energy recovery systems using temperature difference ratio method and related methods

Abstract

The present invention relates to a heat transfer control optimization method (S100) with method steps and variations for controlling brine flow pump (46) in an air handling unit with a run around coil system (20, 21, 23) with differential temperature measuring sensors (30, 24) at outdoor air (22) to supply air (34), and brine flow temperature sensors (36, 37, 54); and optionally a brine flow (43) and an interface to optional supply air flow sensor (31), and exhaust air flow sensor (61), or both, as well as an exhaust air (64) temperature sensor (63). The method is executed by a control system (70) with or with the use of an optional correction table (76) that may support fast and adaptive control of a brine flow control signal (73) controlling the brine flow pump (46) or valves (42, 53) for temperature exchange efficiency optimization. The control method (S100) may operates in a fast controlling method (S200) using a differential temperature method (S210) or a capacity rate method (S220), and then according to a correction method by incrementally adjust and fine tune the brine flow control signal (73) to reach the lowest possible exhaust air (64) temperature as sensed by exhaust air temperature sensor (63); while using the brine flow control signal (73) to continuously adjusting the brine flow by actuating a brine flow valve (42, 53), or a brine flow pump (46).

Description

[0001] EFFICIENCY IMPROVEMENT IN LIQUID-COUPLED ENERGY RECOVERY SYSTEMS USING TEMPERATURE DIFFERENCE RATIO METHOD AND RELATED METHODS

[0002] Technical field

[0003] The present invention relates to a control system and method for Air Handling Units with liquid coupled run-around-coil (RAC) system for heat and / or cooling recovery, for a ventilation air conditioning (HVAC) system.

[0004] Background

[0005] Air Handling Units (AHU) are preferably equipped with a heat recovery function. Plate heat exchangers are one option, and rotating heat exchanges are another. For hygienic factors and for flexibility in installation, AHUs equipped with liquid coupled run-around-coil (RAC) are preferable as heat recovery systems. With an AHU with RAC there is no risk of mixing extract air with the outdoor air to supply air flow, as these channels are completely separated as a supply air stream and an extract air to exhaust air stream. The RAC system in a heat recovery mode, transfers heat from the extract air to exhaust air flow side, to the outdoor air to supply air flow side using air-coils and a pump unit for intermediate circulation of brine fluid. The brine fluid is typically a mixture of water and glycol (or any other anti-freezing agents) to avoid freezing during winter as the outdoor air drops below zero.

[0006] The main benefits of RAC systems compared to the other two main heat recovery technologies for AHUs such as rotating -heat-ex changers (RHE) and plate-heat-exchangers (PHE), are explained as follows:

[0007] - Benefits over RHE and somewhat PHE: no risk of air leakage between extract air to the supply air, and therefore no risk for contamination or smell transfer.

[0008] - Benefits over RHE and PHE solutions: AHU parts do not need to be limited to a fixed position, thus offering freedom to select a feasible placement of the supply air channel and the extract air to exhaust air channel. With a RAC, an AHU can easily be split, and the various parts can be located independent of each other.

[0009] - Benefit over PHE: frost control and mitigation is simple and does not affect the air distribution. - Benefit over RHE and PHE: a RAC system can consist of an arbitrary number of extract air to exhaust air, and outdoor air to air supply air units, respectively.

[0010] Benefit over RHE and PHE: fewer components in the air streams, hence simpler to install and service.

[0011] - Benefit over PHE: less installation space required in the AHU.

[0012] Summarizing all aspects of the comparison with PHE and RHE, the unique benefits of RAC are flexibility and full contamination control.

[0013] A detailed study of challenges of controlling liquid coupled heat recovery systems, is found in the scientific article: “Flow rate optimization in run-around heat recovery systems” by Mohammad Mahmoud, Peter Filipsson, Samuel Brunninge, and Jan-Olof Dal enback, with the article available at: https: / / www.sciencedirect.com / science / article / pii / S13594311210102807via%3Dihub

[0014] Looking at drawbacks, both PHE and RAC have a drawback compared to RHE regarding the inability to utilize moisture transfer, but uniquely, RAC has a lower theoretical heat recovery efficiency compared to both RHE and PHE. This is a consequence of introducing more heat transfer steps (air-metal-brine-metal-air) compared to PHE and RHE (air-metal-air). Further, the control of a RAC to achieve the theoretical maximum is complex which means that in practice, the efficiency can be even lower than expected.

[0015] Run-around-coil (RAC) systems have a superior separation of air flow compared to the mentioned heat exchanger alternatives but a challenge with RAC systems is to ensure high efficiency of the heat exchange function during variations in air flow, temperature, humidity, dimensions, temperature shifts, and weather conditions.

[0016] Indirect control systems (diffuse controller targets for example by minimizing exhaust air temperature) have been designed to operate RAC systems with a high efficiency performance but with complexities, and challenges such as slow recovery regulation and response time to deliver requested demands for air conditioning purposes. RAC control system can be costly installations with unstable and sub optimal regulation methods.

[0017] Further, when utilizing direct control systems, such as balancing brine flow against air flow, the control system becomes sensitive to various deficiencies and unknowns, such as measurement errors and actual brine content. Hence, a better method for regulation of RAC systems and more efficient RAC control system for regulation and optimization is needed, and proposed as follows.

[0018] Summary of invention

[0019] The invention is a method with variant methods that regulates the brine flow of the RAC system such that an optimal efficiency is achieved with a robust, responsive, and predictable control system and method.

[0020] It should be noted that the teachings herein apply equally to heat recovery as well as cooling recovery, and that when reference is made to heat recovery, reference is also made to cooling recovery, unless specifically indicated.

[0021] It has been identified that an optimal controlled energy recovery function in a RAC is enabled when the energy transfer between the respective air flows and the brine flow are matched.

[0022] A high heat recovery (or cooling recovery) efficiency can be achieved using a method where the capacity flow ratio from brine to air is matched equally. Similarly, this can be expressed as that the differential temperature between the ingoing and outgoing air over one coil set; matches equally the corresponding temperature difference of brine side over the same coil set.

[0023] The capacity flow ratio method is here referred to as the Capacity Rate Method (CRM), and the Difference Temperature Method is further referred to as the DTM, or the DT method.

[0024] Benefits and technical effects of each of these methods the CRM and DTM are further explained. The CRM and DTM, each have drawbacks leading to the main invention presented namely the Differential Temperature Method Optimized, that is a hybrid method that gives an optimal regulation responsiveness, robustness, and support for either of the DTM and CRM or similar or for example using an optimal combination of DTM and CRM. A basic implementation alternative can include a method implemented as an algorithm controlling a RAC with temperature sensors and brine regulation actuators for DTM or including flow and temperature sensors and brine regulation actuators for the CRM. Another implementation alternative may make use of another direct approach similar to DTM or CRM or correction tables to determine the optimal actuator regulation The DTM and CRM are fast regulating methods, but less feasible for fine-tuning, hence, in the invention these methods are combined with a fine-tuning method that slowly incrementally adjusts the brine flow, to compensate for errors that might affect the main control method. For a quick start up of an AHU with RAC, it is possible to maximize the brine-flow during a time until the system is stabilized and up and running able to use the DTM and CRM, or the incremental fine-tuning methods.

[0025] The teachings herein thus provide a system or method in such a RAC system that utilizes a first tuning (also referred to herein as a primary regulation) manner (DTM (and / )or CRM) which is used to reach a first working point, where “first working point” is defined as the working point where the heat recovery efficiency is maximized according to the primary regulation.

[0026] The first manner is thus utilized to reach a first working point. Then a (second) tuning manner (also referred to herein as a correction method or correction process) is utilized for possible fine-tuning with aim to find a “second working point” where the heat recovery efficiency is higher compared to the first working point, and any fine-tuning (i.e. adaptation) made is then fed back to the first tuning manner to allow for a faster tuning next time the tuning is performed.

[0027] A maximized brine flow is not temperature efficient but can be considered as a good starting point for regulation using DTM or CRM, compared to a zero or sub-optimal brine flow. Hence, a maximized brine flow may also work as a backup state during system failures to control the system during DTM, CTM or incremental fine tuning.

[0028] DTM and CRM have strengths and weaknesses that fit different regulation demands. Hence a combined optimized DTM, the differential temperature method optimized (DTMO) makes use of DTM, CRM and optionally a correction table to bring quick regulation responsiveness, robust regulation, and long-term precision and stability in regulation.

[0029] A RAC system provided with temperature sensors for DTM is presented in Fig. 1. A similar RAC system with added brine flow sensors configured for CRM is presented in Fig. 2.

[0030] The RAC systems depicted in Fig. 1 and Fig. 2 are provided with liquid-to-liquid heat exchangers to receive heat or cooling recovery from a central liquid flow in an HVAC system installation. The heat recovery efficiency of a RAC controlled by the DTM using differential temperature is presented in Fig. 3. Similarly, the heat recovery efficiency of the CRM using relative capacity flow rate between liquid and air, is presented in Fig. 4.

[0031] In both the DTM and CRM, the heat recovery efficiency peaks at a relative factor equal to 1 and drops drastically to the left as the brine flow is insufficient. Both methods also show a reduced temperature efficiency when the brine flow is exaggerated. An optimal method, the Differential Temperature Method Optimized (DTMO) quickly regulates towards a temperature efficiency optimum, while gradually improving the optimization, and providing robustness to disturbances in flows, variations in brine glycol type and concentration in water, and measurement errors.

[0032] In summary, the DTM provides a method for regulation and control of heat recovery that improves system efficiency, reduces costs, and enhances accuracy by removing the dependence on fluid flow detection devices meanwhile the CRM is dependent on such a fluid flow rate sensor. The optimized DTMO makes use of the temperature and fluid sensors during different control and regulation situations, to optimize the temperature efficiency of the RAC 20.

[0033] Technical problem

[0034] The technical problem for the invention is to provide an AHU with RAC (20) with a brineflow control method for optimal temperature efficiency [%]; that is robust and less influenced by variations in air flow, glycol concentration in brine fluid, precision in sensors and cost of high precision sensors, and that is fast and robust for RAC brine flow control, and that provides for a long-term optimization of the temperature efficiency.

[0035] Solution to problem

[0036] The solution is to provide corrections to a primary control algorithm for RAC control. In some embodiments the primary control algorithm is the differential temperature method (DTM). In some embodiments the primary control algorithm is the capacity rate method (CRM). In some embodiments the primary control algorithm is a similar, fast regulating control algorithm optimization method to control the energy (i.e. temperature) efficiency by means of regulating the brine flow. The advantage of the primary control algorithm is that it is fast, but the disadvantage is that it can generate errors, due to measurement errors, changed conditions, variation in brine flow glycol content, and similar factors. Therefore, it is necessary to correct the brine flow via pump or actuator control to achieve and maintain maximum energy efficiency. The correction method chosen (that is to control brine flow towards an optimum temperature parameter, exemplified throughout the disclosure herein as controlling to obtain the lowest maintainable exhaust air temperature) is a slow control process, but also a robust method within limited variations. Hence, the correction method is not suitable for a primary regulation but, the correction method is proven excellent for corrections.

[0037] The RAC may, in some embodiments, be used as a heat recovery system, and some examples of what or which temperature param eter(s) to optimize for the heat recovery function are given below.

[0038] The RAC may alternatively or additionally (the same system can do both depending on settings and current control), in some embodiments, be used as a cooling recovery system, and some examples of what or which temperature parameter(s) to optimize for the cooling recovery function are also given below.

[0039] Starting with RACs configured as heat recovery systems, one example of a correction method proposed is to optimize towards the lowest exhaust air temperature possible, i.e. minimize the exhaust air temperature.

[0040] Another example of a correction method proposed is to optimize towards the highest supply air temperature possible, i.e. maximize the supply air temperature.

[0041] If the regulation falls outside of the capacity of each regulation method, the method will switch to a more favorable method for optimization; which brings further robustness, responsiveness, and optimization performance.

[0042] As an alternative to optimizing towards the lowest exhaust air temperature possible, one other example is where the temperature parameter is the temperature difference between the extract air temperature and the exhaust air temperature and the correction process is to optimize towards the highest temperature difference between the extract air temperature and the exhaust air temperature (i.e. maximize the temperature difference between the extract air temperature and the exhaust air temperature). This follows the same general principle as optimizing for the lowest exhaust air temperature, but is also taking variations of the extract air temperature into account which (in some cases) makes the correction more stable.

[0043] As another alternative the temperature parameter is a highest supply air temperature, and the correction process is optimizing for the highest supply air temperature, i.e. to maximize the supply air temperature.

[0044] As another alternative the temperature parameter is the temperature difference between the supply air temperature and the outdoor air temperature and the correction process is optimizing for the highest temperature difference between the supply air temperature and the outdoor air temperature, i.e. to maximize the temperature difference between the supply air temperature and the outdoor air temperature. This follows the same general principle as optimizing for the highest supply air temperature, but is also taking variations of the outdoor air temperature into account which (in some cases) makes the correction more stable.

[0045] Continuing with RACs configured as cooling recovery systems, one example of a correction method proposed is to optimize towards the highest exhaust air temperature possible, i.e. maximize the exhaust air temperature.

[0046] Another example of a correction method proposed is to optimize towards the lowest supply air temperature possible, i.e. minimize the supply air temperature. If the regulation falls outside of the capacity of each regulation method, the method will switch to a more favorable method for optimization; which brings further robustness, responsiveness, and optimization performance.

[0047] As an alternative, one other example is where the temperature parameter is the temperature difference between the exhaust air temperature and the extract air temperature and the correction process is to optimize towards the highest temperature difference between the extract air temperature and the exhaust air temperature (i.e. maximize the temperature difference between the exhaust air temperature and the extract air temperature ). This follows the same general principle as optimizing for the highest exhaust air temperature, but is also taking variations of the extract air temperature into account which (in some cases) makes the correction more stable.

[0048] As another alternative the temperature parameter is the temperature difference between the outdoor air temperature and the supply air temperature and the correction process is optimizing for the highest temperature difference between the outdoor air temperature and the supply air temperature, i.e. to maximize the temperature difference between the outdoor air temperature and the supply air temperature. This follows the same general principle as optimizing for the highest supply air temperature, but is also taking variations of the outdoor air temperature into account which (in some cases) makes the correction more stable.

[0049] In some embodiments Correcting the brine flow is performed through correcting the control signal (73).

[0050] In some embodiments the method further comprises updating the primary control algorithm based on a correction found by the correction process and again controlling the brine flow of the RAC (20, 21, 23) utilizing (S210, S220) the updated primary control algorithm for temperature efficiency control (83, 93).

[0051] In some embodiments utilizing (S210, S220) the primary control algorithm includes (S210, S240) utilizing a differential temperature method controlling the brine flow control signal (73) for temperature efficiency control (83).

[0052] In some embodiments utilizing a differential temperature method includes controlling a brine flow control signal (73) for maintaining the differential temperature over an air side and a brine side of coils, respectively, as equal as possible, (54, 36) at 0.8 to 1.4 preferably at 1.0 for temperature efficiency control (83).

[0053] In some embodiments utilizing the DTM further comprises regulating the brine flow of the RAC (20, 21, 23) using the DTM by controlling the brine flow of the RAC (20, 21) controlling a valve (52, 42) or by controlling a brine flow pump (46) such that the temperature difference between a supply air stream temperature sensor 30 and an Outdoor air stream temperature sensor (24) reaches the same temperature difference as between the first brine temperature sensor 54 and the (second) brine temperature sensor (36) whereby the DTM is finished.

[0054] In some embodiments wherein utilizing (S210, S220) the primary control algorithm includes (S220, S250) utilizing a capacity rate method controlling the brine flow control signal (73) for temperature efficiency control (93).

[0055] In some embodiments utilizing the capacity rate method for temperature efficiency control (93) includes controlling the brine flow control signal (73) for maintaining the capacity flow rate on the air side and brine side of the coils, respectively, as equal as possible (32) (54, 37, 43).

[0056] In some embodiments utilizing (S210, S220) the primary control algorithm using the capacity rate method includes controlling the brine flow of the RAC (20, 23) by controlling a valve (52, 42) or by controlling a brine flow pump (46) such that the capacity rate of the supply air stream and the brine flow reaches the same magnitude, or alternatively the capacity flow rate reaches unity, whereby the CRM is finished.

[0057] In some embodiments utilizing (S210, S220) the primary control algorithm further comprises (S240) regulating with compensation or correction from a Correction Table (76), wherein the correction table is configured to translate a temperature difference of the air supply flow, and a temperature difference of the brine flow, into a brine control actuator control signal that controls the brine flow.

[0058] In some embodiments utilizing (S210, S220) the primary control algorithm further comprises (S250) regulating with compensation or correction from a Correction Table (76), wherein the correction table is configured to translate a capacity rate of the air supply flow, and a capacity rate of the brine flow, into a brine control actuator control signal that controls the brine flow.

[0059] In some embodiments Controlling the brine flow of the RAC S200 utilizing the primary control algorithm further comprises: (S230) Regulating using a table method to control brine flow using correction a table (79) to realize the differential temperature method, or capacity rate method further comprises: (S2310) Correcting brine flow with fine tuning using offset; (S2320) Optionally correcting brine flow using extra parameters for differential temperature method; (S2330) Fine-tuning using sensor data; and (S2340) Receiving extra sensor data: air exhaust temperature.

[0060] In some embodiments the method further comprises: (S2370) Updating correction table, where in correction values are improved and updated for improved brine flow control signals for differential temperature parameters, or brine flow control signals (73) for capacity rate parameters.

[0061] In some embodiments Regulating using a table method to control brine flow using correction a table (79) to realize the differential temperature method, or capacity rate method (S230) further comprises: (S2350)Updating correction table using advanced sensor data; (S2370) Updating correction table; and (S2380) Updating correction table using advanced sensor data and knowledge.

[0062] In some embodiments the method further comprises: (S3110) Enable calibration correction when air flow exists; (S3120) Enable calibration correction when brine flow exists;

[0063] (S3130) Enable calibration correction when differential temperature method provides stability in regulation with control error close to zero, or (S3135) Enable calibration correction when capacity rate method provides stability in regulation with control error close to zero.

[0064] In some embodiments the method further comprises starting the primary control algorithm by maximizing the brine flow control signal (73) for a maximal brine flow, to ensure energy efficiency (SI 50) is preceding Controlling the brine flow of the RAC (20, 21, 23), during start up when sensor parameters are unknown; or as a backup fault handling state.

[0065] According to one aspect there is provided a control system (70) comprising: a processing unit (70), a memory (78) configured to a store control program data (78); an interface to an air flow sensor and / or an interface to one or more temperature sensors, such as an exhaust air temperature sensor (63) and / or an extract air temperature sensor (57); an interface to a brine flow sensor (43); the control system being characterized in that the control system is configured to execute any method according to herein.

[0066] According to one aspect there is provided a run around coil system (20, 21) comprising a control system (70) wherein the run around coil system comprises: an interface to the control system (70) comprising input signals from sensors (72); at least one outdoor air (22) to supply air (34) flow heat exchanger (26, 28) configured for heat exchange with a brine flow circuit (41); at least one extract air (56) to exhaust air (64) flow heat exchanger (58, 60) configured for heat exchange with the brine flow circuit (41); one or more temperature sensors, such as an exhaust air temperature sensor (63), an air flow sensor and / or an extract air temperature sensor (57); and the brine flow circuit (41) comprises a brine flow pump (46) or at least a valve (42, 52) configured for brine flow control over the at least one of said heat exchangers (26, 28, 58, 60). Temperature efficiency is defined as in the standard SS-EN 3058:2022; the transfer of sensible heat from exhaust to supply air.

[0067] Brine is defined as a low-freezing-point liquid used to transfer heat in refrigeration, cooling recovery, or heating systems, being a liquid solution, typically water mixed with salts (such as sodium chloride or calcium chloride) or other antifreeze agents (like ethylene glycol or propylene glycol).

[0068] In HVAC, a heat recovery system is a technology or setup that recovers waste heat from for example ventilation air or other heat sources, and repurposes it for useful heating, preheating, or power generation.

[0069] In HVAC, a cooling recovery system is a system that recovers surplus cooling capacity or chilled energy and redirects it for useful purposes, such as pre-cooling incoming air, reducing cooling loads elsewhere, or improving overall thermal management.

[0070] A temperature difference between a temperature A and a temperature B, is defined as, unless otherwise specified, the absolute value of the subtraction of temperature B from subtraction A; |TA-TB|.

[0071] Brine flow control in HVAC systems refers to the regulation and management of the flow rate of brine (a chilled or antifreeze solution) within the system to ensure optimal heat transfer, temperature control, energy efficiency, and system protection. In HVAC systems, especially those involving indirect cooling loops, brine (such as glycol-water mixtures) is used as a secondary refrigerant. Brine flow control involves the use of components like: Pumps - to drive flow, Valves (manual, motorized, or thermostatic) - to regulate flow paths and rates, Flow meters and sensors - to monitor actual flow, and Control systems - to adjust flow based on demand or system conditions.

[0072] Definitions for features, parameters or other terminology that are not specifically defined herein (and also alternative definitions for features, parameters or other terminology that are not specifically defined herein) may be found in in the scientific article: “Flow rate optimization in run-around heat recovery systems” by Mohammad Mahmoud, Peter Filipsson, Samuel Brunninge, and Jan-Olof Dal enback, with the article available at: https: / / www.sciencedirect.com / science / article / pii / S13594311210102807via%3Dihub Or in the European standard SS-EN 308:2022: Heat exchangers - Test procedures for establishing performance of air to air heat recovery components.

[0073] Advantageous effects of the invention

[0074] The differential temperature method (DTM) is equivalent to the capacity rate method (CRM) when it comes to achieving high efficiency. The benefits of the DTM are robustness to fluid properties, sensor robustness and simplicity. Both the brine flow sensor and an optional supply air flow sensor 31, an optional exhaust air flow sensor 61, or both air flow sensors 31, 61, or an indirect air flow estimation based on air flow capacity of supply air fan 32, and exhaust air fan 62 at for example a certain speed, RPM, can be removed which improves the cost, and reduces problems related to measurement uncertainties and sensor drifts; since temperature sensors are more robust and precise compared to brine flow sensors. Another major benefit is that the density and specific heat capacities of brine and air are no longer needed in the control loop, which means that the DTM is insensitive to glycol concentration variations on the brine side which is a major source of uncertainty in a tested product solution.

[0075] When it comes to cost, the supply air flow sensors 31, exhaust air flow sensor 61, or both, and brine flow sensors though costly may be essential for other AHU functions and may therefore not be eliminated. The extra brine flow sensor 43, though useful for other reasons, can completely be eliminated when using the differential temperature method (DTM). The capacity rate method (CRM) will need a brine flow sensor 43, and the differential temperature method optimized (DTMO) may also improve its precision and control robustness using the extra brine flow sensor 43, which is often integrated 39 with a temperature sensor 37 and a brine flow valve 42. The extra temperature sensors are also already in use for other functions, which means that the control method does not need any additional hardware. A simple cost calculation yields a significant cost saving per unit during manufacturing.

[0076] On the other hand, DTM is very sensitive to measurement errors, and even though temperature sensors can be accurate, the accuracy is highly dependent on sensor placement in AHUs, due to air stratification. Fluids are also influenced by ambient conditions. Hence, errors of one or a couple of degrees on total control target must be expected, which will have a large influence on the performance of DTM, especially at relatively high outdoor air temperatures, where the actual temperature difference over the coils is small. In worst case scenario, the error can be larger than the absolute differential temperature measurement.

[0077] Hence, neither of the two primary RAC control methods mentioned (DTM or CRM) are sufficient on their own to find the optimum efficiency point when all potential errors and unknowns are considered. This motivates the use of the proposed correction method as an add-on.

[0078] Brief description of drawings

[0079] The invention is described, by way of example, with reference to the accompanying drawings, which follows.

[0080] Fig. l is a first embodiment with a schematic description of a run-around-coil (RAC) system with temperature sensors measuring outdoor air temperature 22 using outdoor air temperature sensor 24, and supply air temperature 34 using supply air temperature sensor 30, as well as brine temperature sensors 54 and 36 measuring brine temperature change over brine to air heat exchangers 26, 28. Heat recovery is enabled by transferring heat to the supply side 34, with exchangers 58, 60 connecting the brine flow with the extract air 56 to the exhaust air flow 64, preferably with an exhaust air 64 temperature sensor 63 and / or an extract air temperature sensor 57. The control system 70 is configured to optimize and control at least the brine flow pump 46 or flow control.

[0081] Fig. 2 is a (second) embodiment with a schematic description of a run-around-coil (RAC) system with an optional outdoor air temperature sensor 24 measuring outdoor air temperature 22 and / or an optional supply air temperature sensor 30 measuring supply air 34 temperature, as well as brine temperature sensors 54 measuring brine temperature entering the heat exchangers 28, 26, before reaching brine temperature sensor 37, and brine flow sensors 43; usually combined with a (second) three-way valve for brine flow temperature control 42 valve, into a temperature and flow-controlled valve unit 39. Heat recovery is enabled by transferring heat to the supply side 34, with heat exchangers 58, 60 connecting the brine flow with the extract air 56 to exhaust air flow 64, with an optional exhaust air temperature sensor 63 and / or an optional extract air temperature sensor 57. The control system 70 is configured to optimize and control at least the brine flow pump 46 or flow control. Fig. 3 is a diagram 80 presenting temperature efficiency 81 at different relative temperature difference over coil air and liquid sides 82, that is the brine flow, with optimal temperature efficiency at a 1 to 1 relation between air stream and brine stream temperature difference over RAC coil. Region 84 shows a too low, or slow, brine flow for temperature efficiency. Region 85 shows a too fast, or high, brine flow for temperature efficiency.

[0082] Fig. 4 is a diagram 90 presenting temperature efficiency 91 at different relative capacity flow rate over coil air and liquid sides 92, that is the brine flow, with optimal temperature efficiency at a 1 to 1 relation between air stream and brine stream capacity flow rate 93. Region 84 shows a too low, or slow, brine flow for temperature efficiency. Region 85 shows a too fast, or high, brine flow for temperature efficiency.

[0083] As noted in the above, the main example focused on for the correction process during heating mode is to optimize for the temperature parameter being a lowest temperature of exhaust air 64 for example as measured by the exhaust air temperature sensor 63. However, it should be noted that the same method may be applied also to the other disclosed (and undisclosed) alternative correction process, namely: to optimize for the temperature parameter being a highest temperature of supply air 34 for example as measured by the supply air temperature sensor 30; to optimize for the temperature parameter being a highest (positive) temperature difference between extract air 56 (for example as measured by the extract air temperature sensor 57) and exhaust air 64, i.e. Textract - Texhaust (or a lowest (negative) temperature difference between exhaust air 64 and extract air 56, i.e. Texhaust - Textract); and / or to optimize for the temperature parameter being a highest (positive) temperature difference between outdoor air 22 (for example as measured by the outdoor air temperature sensor 24) and supply air 34, i.e. Toutdoor - TSUppiy (or a lowest (negative) temperature difference between supply air 34 and outdoor air 22, i.e. TsuPPiy - Toutdoor).

[0084] In other words to maximize the temperature difference(s) | Texhaust Textract | and / or | Tsupply T outdoor | •

[0085] The same general corrections also apply for cooling recovery, but vice versa for the single temperatures; exhaust temperature and supply air temperature, i.e. maximizing supply air temperature during heat recovery becomes minimizing supply air temperature during cooling recovery mode and maximizing exhaust temperature during heat recovery becomes minimizing exhaust temperature during cooling recovery mode. When the temperature difference is defined as the absolute value of the subtraction of one temperature from the other, the correction processes based on temperature differences become the same for cooling recovery as for heat recovery.

[0086] As indicated it is also possible to combine the corrections, i.e. to optimize for more than one temperature parameter at a time. As an optimal working point is optimal, it will be the same working point irrespective of which correction process is used. And in some situations, one correction process may be able to get closer than another. It is also possible in some embodiments to switch from optimizing for one temperature parameter to optimizing for another temperature parameter. Such a switch may be done in case the optimization has not finished (reached its target) within a predetermined number of iterations.

[0087] A correction process is thought to reach its target (i.e. finish) when the difference between two subsequent readings of the temperature parameter is below a threshold value. The threshold value may be different for the different temperature parameters.

[0088] Fig. 5 is a flow chart representing a method for run-around-coil RAC regulation SI 00 for an Air Handling Unit comprising:

[0089] S200 Regulating the RAC system using the primary (first) control algorithm (such as DTM, CRM, or Table method) to control the brine flow; and

[0090] S300 Correcting the brine flow control signal utilizing the (second) correction process which is configured for optimizing for a temperature parameter, such as a lowest exhaust air 64 temperature at sensor 63 (although not limited to this example, but also applicable to the other examples given herein). The correction process is iterated using an incremental process to control the brine flow. The method also comprises (continuously) Regulating the brine flow by actually controlling the actuators S400 using the brine flow control signal.

[0091] In some embodiments Correcting S300 comprises Testing if preconditions for correcting brine flow are fulfilled S310. In some embodiments the testing includes a test - Test a: if to increase brine flow S320. In some embodiments the testing includes a test - Test b: if to decrease brine flow S330. The testing also, in some embodiments, includes a test or rather Identification of the best correction, within an allowed regulation range. The identification is in some embodiments based on the number of steps that does not improve optimization S340 by Using the maximal correction effect allowed, to introduce inertia in regulation S3410.

[0092] In some embodiments Regulating the brine flow using the brine flow control signal S400 optionally comprises Regulating brine flow using the brine flow control signal determined by the primary control algorithm (differential temperature method or capacity rate method or other) with correction optimization S410.

[0093] Fig. 6 is a flow chart representing five regulation methods S200 for regulating using differential temperature method (DTM) S210, the capacity rate method (CRM) S220, and the Table method S230 with variations combining DT method S240 respectively the CRM S250 with the usage of a Correction Table 76. Regulating using table method may also comprise a step S2370 updating correction table, to further increase the precision of the correction table for DT S240 and CRM S250 table methods making use of the correction table 76.

[0094] Step S230 Regulating using table method to control brine flow, further comprises the steps: S2310 Correcting brine flow with fine tuning using offset, to incrementally adjust the brine flow control signal as small offset steps; optional step S2320 Correcting brine flow using extra parameters for DT method, such as extra sensor data measuring temperature differences, brine flow or air flow; step S2330 Fine-tuning using sensor data, adjusts sensor data as input to the regulation process for fine tuning; step S2340 Receiving extra sensor data “air exhaust temperature” as input sensor parameter for later fine tuning optimization towards “a lowest air exhaust temperature”; and finally step S2370 Updating correction table, where the correction table 76 is updated based on optimizations made as a correction and learning process. All mentioned steps may determine its control decision based on correction table data found in the Correction Table 76. For earlier recorded temperature and brine flow parameters are stored in the Correction Table 76, thus allowing a look up of the most feasible brine control parameter for the control situation and state. Correction table 76 may be implemented as an extended Kalman Filter (EKF).

[0095] Fig. 7 is a flow chart for a method that is configured to regulate using table method, that is using the correction table 76 to look up correction values and control the brine flow, that is step S230 Regulating using table method to control the brin flow, with mandatory sub steps S2310, S2340, and optional sub steps S2320, S2350, S2370, and S2380.

[0096] Fig. 8 is a flow chart representing the method step Testing if preconditions for correcting brine flow are fulfilled S310, using the following sub steps: S3110, S3120, S3130, optionally sub step S3135, and mandatory sub steps S3140, S3150, and S3160. Fig. 9 is a flow chart representing the method step S400, regulating brine flow using brine flow control signal, comprising sub step S410 Regulating brine flow actuator using earlier determined brine flow control signal, determined for the DTM or CRM with correction optimization; followed by sub steps S4210 Fine tuning of brine flow using offset on pump control, S4220 Regulating brine flow extra parameters for DTM, or CRM using for example a PID regulator, and optional sub steps S4230 Fine tuning of sensor data correction data for sensor data processed by the DTM or CRM, and S4240 Tuning of brine flow using calibration data from zero flow temperature control.

[0097] Fig. 10 is a flow chart representing method step S700, that is Calibrating sensors by regulating brine flow using the DT method to control brine flow plus calibration data comprising a sensor calibration step; and using sensor calibration correction data in DT method as temperature sensor input. S700 comprises the parallel sub steps S710 and S720, followed by sub step S730, and optional sub step Reporting or raising an alarm relating to deviations in heat capacity when large correction needs are indicated in step S710 to S730 then a fault regarding too high or too low glycol percentage may be indicated and reported to a super- visioning system or operator S740. An alarm can be raised to an operator of the HVAC system or transmitted to an interfaced super-visioning system when unexpected large control during fine-tuning deviations is needed, that reach beyond 98%, preferably beyond 99% of normal control range. Even though a zero-point calibration cannot tell, if the brine has a too high or too low percentage of antifreeze, or anti-rust agent such as glycol, an alarm can be raised when the fine-tuning, and even during a table method, when the fine-tuning starts to deviate. Reasonable causes could be incorrect brine mix, leakage of circuit that has been compensated for with refilled water, or too much glycol.

[0098] Fig. 11 shows the control system 72 with interfaces for sensors 24, 30, 36, 37, 47, 54, 43, and actuators 42, 45, 62, 32,46 for an air handling unit for RAC system, with the master method typically implemented as software 78, in a control system 70, preferably with support of a table 76, comprising the method step SI 00 Method for RAC regulation, for the control system, with dotted lines for optional method step SI 50, mandatory sub step S200, optional sub step S300, and mandatory sub steps S400, and possible state changes S500, S600, and S610. The main regulation may use the DTM or CRM method with or without support from a table method. Description of embodiments

[0099] Embodiments of the invention are described as follows.

[0100] In an embodiment, the invention is a method for controlling an air handling unit (AHU) with a liquid-coupled run-around-coil (RAC) heat recovery system, comprising the following steps S200, S300 and S400. S200 is a step that comprises at least the usage of the differential temperature method DTM S210 or the capacity rate method CRM S220 for fast and robust adjustment of the brine flow control signal that in step S400 regulates and controls at least one valve actuator, and or brine pump. When the brine flow has been roughly and robustly adjusted and cannot improve the temperature efficiency of the RAC temperature exchange, a fine-tuning method step S300 is activated to improve the temperature efficiency further and slowly, if possible. In step S300, optimization of the temperature efficiency is made as a finetuning regulation and control of the brine flow, i.e. through the correction process, towards a temperature parameter for example a minimized exhaust air 64 flow temperature at temperature sensors 63 (although not limited to this example, but also applicable to the other examples given herein). This fine-tuning step, i.e. correction process, provides a correction that is kept if the temperature efficiency does not degrade. The control signal will thus be the control signal as determined through the primary regulation algorithm and adapted ( / corrected) by the (second) correction process.

[0101] When the temperature efficiency degrades in step S300, the method may further return to control the brine flow based on the DTM or CRM, or even a combination, but with the correction overlaid.

[0102] As will be later described, the DTM and CRM control logics may be implemented using a correction table 76, as in the correction table version of DTM S240 and CRM S250 methods. A benefit of using a correction table is that it is an easy way to implement a predictable control system, quick to calculate using look up of values, and that the correction table itself may be further optimized by updating the correction table with new knowledge S2370.

[0103] A basic version of the invention, a method for controlling an air handling unit (AHU) with a liquid-coupled run-around-coil (RAC) heat recovery system, comprising the following: controlling using a S200 primary control algorithm, (iteratively) correcting using a correction method. When the best available regulation (heat exchange) is achieved, through the correction, the adaptation made (i.e. the correction) is fed back to the primary control algorithm whereby the primary control algorithm is adapted accordingly. For example, the adaptation made by the correction process may be an increased or decreased flow of the brine, and the primary control algorithm is adapted using the correction (being an increased or decreased flow of the brine) as an offset (so the starting point for the control of brine is adapted with the offset). The process may be repeated repeatedly until no further improvement is made (i.e. until the change between two resulting brine flows is under a threshold level (or results in a same brine flow)).

[0104] Some more details are discussed below.

[0105] S200 Controlling the brine flow of the RAC 20, 21, 23 by, as one alternative:

[0106] S210, S240 Utilizing a differential temperature method controlling a brine flow control signal 73 for maintaining a differential temperature over the air side and brine side of the coil, respectively, as equal as possible as a difference between the brine flow temperature sensors 54, 36 at 0.8 to 1.4 preferably at 1.0 for temperature efficiency control 83. The value range 0.8 to 1.4, represents the relative temperature difference over coils air / liquid. Liquid means brine. This means that the regulation of the brine flow should be increased or decreased to reach the peak of temperature efficiency 83 in Fig 3.

[0107] Well-known control algorithms can be used as well as mechanism such a PID regulators, to determine if to reduce or increase the brine flow. A most basic method is to reduce the brine flow if relative temperature over the coils as air / liquid is beyond 1; that is the temperature difference of the air flow Outdoor air to Supply air compared to the brine flow's temperature difference over the RAC coil's heat exchanger with the air flow.

[0108] Also if the relative temperature difference over coils air / liquid is less than 1, then the DTM is to increase the brine flow control signal.

[0109] Alternatively the method could make use of the capacity rate method CRM for controlling the brine flow of the RAC 20, 21, 23 as follows in S220, and S250:

[0110] Utilizing a capacity rate method controlling the brine flow control signal 73 for maintaining the capacity flow rate on the air side and brine side of the coils respectively, as equal as possible over the coil's air flow capacity rate 32 and the brine flow capacity rate 54, 37, 43 at 0.8 to 1.3, preferably at 1.0 for temperature efficiency control 93.

[0111] This means that if the brine flow capacity rate difference for the liquid side of the coil relative the air flow, as described in Fig 4, is less than 0.8, then the brine flow control signal 73 is increased, and if the brine flow capacity rate difference between liquid and air is over 1.3 then the brine flow control signal 73 may be decreased. When the primary control algorithm (DRM or the CRM or other) reaches its target (which might due to various errors be different from the real optimal operation point), i.e. the primary control algorithm finishes its tuning of the brine control signal, the method in the innovation switches to a more slow fine-tuning method - the (second) correction process, where optimization for efficiency is made by monitoring a temperature parameter and optimize the temperature parameter.

[0112] As one example for when the RAC is configured for heat recovery, the monitored temperature parameter is the exhaust air temperature for example as sensed by the exhaust air temperature sensor 63, and the optimization of the temperature parameter is to minimize / optimize towards a lowest (possible) exhaust air temperature, for example when a sufficient supply air flow 34 and extract air flow 56 is supported. Such a lowest exhaust air temperature indicates that the highest amount of energy is transferred, thus indicating that the highest possible temperature efficiency is reached.

[0113] As an alternative to optimizing towards the lowest exhaust air temperature possible, one example is to optimize towards the highest temperature difference between the extract air temperature (for example as sensed by the extract air temperature sensor 57) and the exhaust air temperature (for example as sensed by the exhaust air temperature sensor 63). This follows the same general principle as optimizing for the lowest exhaust air temperature but is also taking variations of the extract air temperature into account which (in some cases) makes the correction more stable.

[0114] As another example, the monitored temperature parameter is the temperature of the supply air 34 for example as sensed by the supply air temperature sensor 30, and the optimization of the temperature parameter is to maximize / optimize towards a highest (possible) supply air temperature, for example when a sufficient supply air flow 34 and extract air flow 56 is supported. Such a highest supply air temperature indicates that the highest amount of energy is transferred, thus indicating that the highest possible temperature efficiency is reached.

[0115] As an alternative to optimizing towards the highest supply air temperature possible, one example is to optimize towards the highest temperature difference between the outdoor air temperature (for example as sensed by the outdoor air temperature sensor 24) and the supply air temperature (for example as sensed by the supply air temperature sensor 30). This follows the same general principle as optimizing for the highest supply air temperature but is also taking variations of the outdoor air temperature into account which (in some cases) makes the correction more stable.

[0116] As mentioned above, the opposite temperature parameters may be used when the RAC is configured for cooling recovery, wherein minimizing the temperature parameter being the exhaust air temperature becomes maximizing the exhaust air temperature; maximizing the temperature parameter being the supply air temperature becomes minimizing the supply air temperature, maximizing the temperature parameter being the temperature difference between extract air temperature and exhaust air temperature becomes maximizing the temperature difference between exhaust air temperature and extract air temperature, and maximizing the temperature parameter being the temperature difference between supply air temperature and outdoor air temperature becomes maximizing the temperature difference between outdoor air temperature and supply air temperature.

[0117] Thus, in some embodiments the (second) correction process 300 further comprises: Correcting the brine flow control signal 73 by optimizing a temperature parameter, for example for lowest exhaust air temperature (although not limited to this example, but also applicable to the other examples given herein) through iterative adjustments using an incremental process to control the brine flow control signal 73provided by the primary control algorithm (S210, S220). The incremental process may in some embodiments be implemented as performing an adjustment, noting of the exhaust temperature is increased or decreased. If the exhaust temperature is decreased, a same (or smaller) adjustment is made to (hopefully) further decrease the exhaust temperature. If the exhaust temperature is increased, a reverse (or reverse and smaller) adjustment is made to (hopefully) decrease the exhaust temperature. In some embodiments the iterative process may be terminated after a predetermined number of adaptations. In some such embodiments, each adaptation is of a smaller size.

[0118] In some embodiments the iterative process may be terminated after the result of the adjustment is below a threshold amount (i.e. for the example of optimizing for a lowest exhaust air temperature; current exhaust temperature - previous exhaust temperature <= threshold amount) or the adjustment has been decreased (become smaller) than a threshold level (current adjustment - previous adjustment <= threshold level). It should be noted that when comparing adjustments as regards “smaller”, only the absolute value is compared (|adjustment|).

[0119] For embodiments where the optimization is for a lowest temperature parameter, the following tests are performed: If a decrease is followed by an increase in temperature parameter (such as exhaust air temperature), a smaller adjustment is made but in reverse (positive becomes negative and vice-versa), where smaller may be 25%, 50%, 75% 80%, 85%, 90% or 95% of the previous adjustment. Similarly, for embodiments where the optimization is for a highest temperature parameter, the following tests are performed: If an increase is followed by a decrease in temperature parameter (such as supply air temperature), a smaller adjustment is made but in reverse.

[0120] In some embodiments the adjustment is in brine flow (or the control signal regulating the brine flow). A positive adjustment may thus be seen to increase the brine flow, and a negative adjustment to decrease the brine flow.

[0121] During each control loop, the brine flow control signal 73 is sent or transmitted to regulate S400 and adjust the brine flow of the RAC. Such adjustment can be made by adjusting a brine flow circuit valve, or a brine-flow pump: Regulating the brine flow 46 using the brine flow control signal 73.

[0122] In some embodiments the (second) correction process, i.e. Correcting brine flow control signal S300 by optimizing for a temperature parameter (such as lowest exhaust air 64 temperature at sensor 63) through iterative adjustments using an incremental process to control the brine flow control signal generated by the primary method thus comprises testing that may comprise S310, S320, S330, and S340 as follows:

[0123] S310 Testing if preconditions for correcting brine flow are fulfilled, that means that if the primary control algorithm (DTM or CRM or other) does not deliver further optimization improvements, or have stabilized, then the fine-tunning of the (second) correction process as described above, may have better chances to further improve and optimize the temperature efficiency of the AHU with RAC.

[0124] Similarly, as for the primary regulation, the (second) correction process iterated. In some embodiments the adjustment for the correction regulation is smaller than the adjustments for the primary regulation, and the corresponding threshold levels and amounts may also or alternatively be smaller for the correction process than the primary regulation.

[0125] Alternatively the iteration is performed for a number of steps noting if the adjustment provides a change in exhaust temperature above a threshold amount or not, noting how many steps do not provide such a change above the threshold amount.

[0126] S320 Next is testing if conditions are fulfilled to increase the brine flow control signal 73, and if a previous increase in brine flow control signal 73 resulted in a further reduced exhaust air 64 temperature 63. If that is the case, then the brine flow control signal 73 can be increased, to then let step S400 actuate and control an increase in the brine flow over the coils of the RAC. As for the iteration of the primary control, a subsequent adjustment (in this case increase) may be smaller than a previous adjustment.

[0127] S330 An alternative is: Testing if conditions are fulfilled to decrease the brine flow control signal 73, and if a previous decrease in brine flow resulted in a further reduced exhaust air 64 temperature 63, and if so then decrease the brine flow control signal 73. As for the iteration of the primary control, a subsequent adjustment (in this case decrease) may be smaller than a previous adjustment.

[0128] S340 Next is: Identifying the best correction of the brine flow control signal 73 within an allowed region, or regulation range, based on the number of control steps that currently have not improved the optimization or alternatively how fast, i.e. the number of iterations needed, the exhaust temperature change is below the threshold amount (i.e. the change is insignificant). The maximum regulation range can be set as a parameter, predetermined or based on previous results, to avoid a too rapid adjustment. The intention is to incrementally adjust the brine flow control signal 73 using minimal steps needed such as 5%, 3% or less preferably in steps less than 1%, to fine-tune the brine flow. Tiny steps and delays are required as the regulation of the exhaust temperature 63 because a minor change in brine flow 42, 52, 46 results in a delayed response.

[0129] Furthermore, Identifying the best correction of the brine flow control signal (S340) may include (S3410) the correction using a maximal correction effect allowed as a limit for each correction occasion for the brine flow control signal 73. That prevents a too fast correction rate beyond the fine-tuning regulation capacity.

[0130] To further improve the tuning of the primary control algorithm for a next or subsequent optimization later or during ongoing operation, the previous control signal determined by the primary control algorithm is used as the starting point for a next tuning done with the primary control algorithm.

[0131] Also, for a next or subsequent optimization later or during ongoing operation, the primary control algorithm may be adapted by the (second) correction process. In some embodiments the primary control algorithm is adapted by the best correction determined by the (second) correction process. In some such embodiments, the best correction is added as an offset to the start of the primary control algorithm. In some alternative such embodiments, the resulting control signal (including the best correction, the best correction being the best adjustment here being an offset for the control signal) is used as the next starting point for the primary control algorithm.

[0132] To illustrate, if the primary regulation starts with a maximum flow rate and then ends up with a flow rate Fo in the allowed range, the correction provides a best correction bO, the new start point may become Fi = Fo + bo.

[0133] This allows for overcoming errors in sensors. Different types of sensor errors have different types of impact on the results since it is a matter if the errors shift the pump operation (i.e. the actuators regulating the brine flow) to be less than or to be more than the balance point where an optimum operation is achieved. Experiments have shown that the influence of measurement error on the energy performance of RAC with DTM may be drastically affected, and even for small errors under “best-case” scenario, an increase of annual energy demand of 10 % can be expected. In the “worst case” scenario, but still with realistic measurement error magnitudes, the energy demand was increased by 25 %. For RAC with CRM, it was found that an annual energy increase of about 15 % compared to error-free operation can be expected.

[0134] The (second) correction process, method or algorithm is thus highly suitable to compensate for sensor errors. As both DTM and CRM is dependent on several sensors and in particular the exact value of these sensors, they are both sensitive to errors in sensors. However, the correction process described herein - being only dependent on a change in sensor reading of a single sensor - is less sensitive to sensor errors.

[0135] The two-step process of applying a primary control algorithm first, which is then corrected disclosed herein is thus highly successful in reducing sensitivity or correcting for sensor errors.

[0136] To summarize, first a primary control algorithm (DTM or CRM or other) is applied providing a suitable working point (control signal) - which is assumed to be optimum by the primary control algorithm. As such a working point (in the allowable range) is reached, the primary control algorithm is finished.

[0137] Then a (second) correcting process is applied which optimizes for a temperature parameter (as exemplified herein, for example lowest exhaust temperature and / or highest supply air temperature) - by changing the control signal at small increments (5, 3, 1 or less than 1 %) until the desired temperature parameter (for example lowest exhaust temperature and / or highest supply air temperature) - within a threshold level - is achieved. The correction process thereby finds a correction to the primary control algorithm.

[0138] The primary control algorithm may then be adapted or updated based on the correction found or made by the correcting process. The adaptation may be to simply add the correction to the control signal of the primary control algorithm or as sensor adjustments.

[0139] The two-step process may, in some embodiments and instances, be applied until no significant change in control signal (above a threshold level) is achieved (possibly within a number of steps).

[0140] The two-step process may also or alternatively, in some embodiments and instances, be applied when there is detected a change in the air flow. The change in the air flow may be related to velocity or rate of airflow. The change in the air flow may also or alternatively be related to a temperature of the airflow.

[0141] The two-step process may also or alternatively, in some embodiments and instances, be applied repeatedly at given time intervals, for example daily, once an hour to mention a few examples. In some embodiments, the change discussed is applied as a change to the brine flow control signal. In some embodiments, the adjustment discussed is applied as an adjustment to the sensor readings, wherein the sensor readings are corrected until an optimum working point is achieved. It should be remembered that if the correction process provides a correction, there is probably an error in one or more sensor readings, as theoretically the primary control algorithm should provide the optimum working point (control signal).

[0142] It should also be mentioned that the two-step process may be applied on both VAV (Variable Air Volume) systems as well as on CAV (Constant Air Volume) systems.

[0143] As mentioned Regulating brine flow S400 may include S410 Regulating brine flow using a differential temperature method with correction optimization; alternatively, or in combination with a method wherein Regulating brine flow S400 includes a step S410 regulating brine flow using a brine flow control signal determined using the capacity rate method; with correction optimization.

[0144] This means that the method can be configured to make use of the DTM, the CRM, or both methods, and then defer the actual control of the brine flow controlling actuators, brine flow pump, or brine-flow valve(s), to adjust brine flow. Hence the DTM and CRM may be operated, as two simultaneously active methods for further optimization, and / or selection of which method to be used based on situation, stability, and accessible available sensors at hand.

[0145] Furthermore, the method may be specialized in that Controlling the brine flow of the RAC S200 further comprises regulating the brine flow of the RAC S210, denoted S210 Regulating the brine flow of the RAC 20, 21, 23 using the differential temperature method (DTM) by controlling the brine flow of the RAC 20, 21 by controlling a valve 52, 42 or by controlling a brine flow pump 46 such that the temperature difference between a supply air stream temperature sensor 30 and an Outdoor air stream temperature sensor 24 reaches the same temperature difference as between the first brine temperature sensor 54 and the (second) brine temperature sensor 36.

[0146] In some embodiments the method may further comprise S240: Regulating using DT method with compensation and correction from a Correction Table 76, wherein the correction table is configured to translate a temperature difference of the air supply flow, and a temperature difference of the brine flow, into a brine control actuator control signal that controls the brine flow.

[0147] By using a correction table 79 that when give parameter values, can look up control parameters for the brine flow correction signal, the method can efficiently, predictable, and quickly select the best brine flow control signal 73, for each situation. Also, the table 79 may easily be adapted and optimized using a feedback loop, or as a self-learning operation.

[0148] Similarly, in some embodiments, the method may further comprise regulation using the CRMS220 wherein Regulating the brine flow of the RAC 20, 21, 23 using the capacity rate method, is controlling the brine flow of the RAC 20, 23 by controlling a valve 52, 42 or by controlling a brine flow pump 46 such that the capacity rate of the supply air stream, or extract air stream, and the brine flow reaches the same magnitude; typically indicated by an equal capacity rate, or equal temperature difference.

[0149] In some embodiments the method further compriseS250: Regulating using capacity rate method with compensation or correction from earlier mentioned Correction Table 76, wherein the correction table is configured to translate a capacity rate of the air supply flow, and a capacity rate of the brine flow, into a brine control actuator control signal that controls the brine flow.

[0150] In some embodiments S200 may further comprise S230 “Regulating, or controlling, using a correction table 79 method to control the brine flow control signal using correction table 79 to realize the differential temperature method, or capacity rate method”, comprising: S2310 Correcting brine flow with fine tuning using an offset.

[0151] S2320 Optionally correcting brine flow using extra parameters for differential temperature method, as a combination of earlier mentioned methods.

[0152] S2330 Fine-tuning using sensor data from temperature sensors, and any flow rate sensors, if any, and;

[0153] S2340 Receiving extra sensor data, air exhaust temperature 63 to further support the fine tuning steps.

[0154] Using the table method, new control strategies can easily and efficiently be introduced to optimize each individual type of AHU installation configuration.

[0155] Furthermore, the method as just described may be specialized in that S230 further comprises S2370, Updating correction table, where in correction values are improved and updated for improved brine flow control signals for differential temperature parameters, or brine flow control signals 73 for capacity rate parameters.

[0156] This mentioned step, would let the AHU control method optimize its own rapid and finetuning algorithms and control, implemented in the control table 79.

[0157] S230 may thus in some embodiments further comprise the following for an automatic learning and adaptation function, for further optimization comprising the sub steps: S2350 Updating correction table using advanced sensor data;

[0158] S2370 Updating correction table; and

[0159] S2380 Updating correction table using advanced sensor data and knowledge.

[0160] To further emphasis the strength of the method, the method may in step Testing if preconditions for correcting brine flow are fulfilled S310 to further introduce the sub-steps S3110, S3120, S3130, S3140, S3150, and S3160 as means for automatic calibration, as the following optional steps:

[0161] S3110 Enable calibration correction when air flow exists;

[0162] S3120 Enable calibration correction when brine flow exists;

[0163] S3130 Enable calibration correction when differential temperature method provides stability in regulation with control error close to zero, or

[0164] S3135 Enable calibration correction when capacity rate method provides stability in regulation with control error close to zero;

[0165] S3140 Cancelling calibration correction when air flow changes, continuously;

[0166] S3150 Increasing number of tries until max number is reached; and then reset number of tries made; and

[0167] S3160 Enable calibration correction when at heat recovery mode.

[0168] For S3130 and S3135, and in general, the calibration may thus be made when there is a correction provided by the (second) correction process.

[0169] The mentioned sub steps conditions and support and state transitions S500, S610, and S600, where different optimization is selected as mainly steps S200, and S300 with sub-steps.

[0170] The method as described may further be specialized in that S400 Regulating brine flow 46 using the brine flow control signal 73, further comprises the following: (S410) Regulating brine flow using the brine flow control signal determined using the differential temperature method or capacity rate method with correction optimization. The correction data can be processed using the Correction Table 76 using: air flow rate, or at a constant air flow rate; then (S4210) Correction of brine flow using offset on pump control; followed by: (S4220) Regulating brine flow extra parameters for differential temperature method, or capacity rate method using for example a Proportional Integral Derivative (PID) regulator, or similar control system. Then, (S4230) Fine tuning of sensor data correction data for sensor data processed together with the differential temperature method or capacity rate method; and (S4240) Tuning of brine flow using calibration data from zero flow temperature control.

[0171] Mentioned steps can be used to further optimize the temperature efficiency for the AHU with liquid coupled heat recovery. Note that other modes and methods of operation will be necessary for cooling recovery, and for frost prevention.

[0172] Further improvements by implementing calibration of sensors are possible and included in some embodiments, by regulating brine flow using the differential temperature method to control brine flow plus calibration data comprising a sensor calibration step; and using sensor calibration correction data in differential temperature method as temperature sensor input. Such a method may comprise:

[0173] S710 Calibrating temperature sensors at air flow from Outdoor Air to Supply Air, with zero brine flow, or the step (S720) Calibrating temperature sensors at brine from Brine-in to Brine-out, with zero air flow as supply side.

[0174] This is then followed by S730 Identifying and setting calibration for usage in differential temperature method, the capacity rate method, or using the table method.

[0175] Finally, a last step S740 Reporting or raising an alarm relating to deviations in heat capacity, can be initiated when: large correction needs are indicated in step S710 to S730 thus indicating a fault regarding too high, or too low, glycol percentage. Such a fault may be indicated and reported to a super-visioning system such as a building automation system, or any other operator interface.

[0176] The method mentioned can be further improved to handle situations during start up and error situations, by adding an initial step (SI 50) that is maximizing the brine flow control signal 73 for a maximal brine flow, to ensure energy efficiency during start up when sensor parameters are unknown, or as a backup fault handling state. This ensures that the brine flow control method is operating at a right-hand side 85 of the optimal temperature efficiency peak 83, as described in Fig. 3 and Fig. 4; that is a preferable operational state when applying the DTM or CRM, as well as the incremental method steps for fine-tuning towards an optimal temperature efficiency peak.

[0177] Also provided is a control system 70 for controlling the operation of an AHU with RAC. The control system 70, may comprises a control computer or electronic logic circuits, or analogue electronics, executing the method as described herein. More specifically the control system 70 comprises: a processing unit, a memory configured to a store control program data, and a control table, more specific implementing the method as described herein; one or more interfaces to temperature sensor(s) such as any of sensors 24, 30, 36, 37, 47, 54, 57, 63, but predominantly to sensor 63; an interface to brine flow sensor 43; an interface to supply air flow sensor 31, or exhaust air flow sensor 61, or both; an interface to brine flow pump control 46; an interface to brine flow valve control 42, 52; an interface to control the outdoor air 22 flow to the supply air flow 34; and an interface to control the extract air 56 flow to the exhaust air 64 flow; wherein the control system 70 is configured to execute the control method SI 00 for an AHU according to herein, to control and optimize energy efficiency of the AHU's liquid coupled run-around-coil (RAC) system; during heat recovery operation.

[0178] There is also provided an Air handling unit (AHU) with a liquid coupled run-around-coil (RAC) 20, 21 system comprising a control system 70 as described herein.

[0179] The run around coil (RAC) system 20, 21 may further comprise one or more of: an interface to the control system 70 comprising input signals from temperature sensors 72; at least one outdoor air 22 to supply air 34 flow heat exchanger 26, 28 configured for heat exchange with a brine flow circuit 41; at least one extract air 56 to exhaust air 64 flow heat exchanger 58, 60 configured for heat exchange with the brine flow circuit 41; an exhaust air temperature sensor 63 and / or an extract air sensor 57; and where in the brine flow circuit 41 comprises a brine flow pump 46 or at least a valve 42, 52 configured for brine flow control over the at least one of said heat exchangers 26, 28, 58, 60. The third embodiment is further specialized in that the control system 70 is configured to execute any method according to herein, that is the method for optimization of temperature efficiency of the RAC according to variants previously described.

[0180] Furthermore, the run around coil (RAC) system 20, 21 for an AHU may be provided specialized in that: the outdoor air 22 to supply air 34 flow heat exchanger 26, 28 is configured for heat exchange with the brine flow circuit 41 which comprises: a temperature sensor for outdoor air flow 24, and a temperature sensor for supply air flow 30. The brine flow circuit 41 further comprises a first brine temperature sensor 54 and a (second) brine temperature sensor 36; and furthermore, the control system 70 is configured to execute any method as earlier described, using the differential temperature method (DTM).

[0181] Alternatively, or in combination previous mentioned RAC system 20, 21 using the differential method (DTM); the run around coil system 20, 23 can be configured for operation using the capacity rate method (CRM); thus, further providing a variation to the RAC system. Such a RAC system configured for CRM, may further be specialized in that the brine flow circuit 41 of the RAC comprises: a brine flow sensor 43; and an optional (second) brine temperature sensor 36, 37 or an optional third brine temperature sensor 47, and a supply air flow sensor 31, or exhaust air flow sensor 61, or both, that may be integrated in an air pump / fan for extract air 32 or for supply air 62; all configured as input to the capacity rate method; with the unique feature that the control system 70 is configured to execute any method as is described herein, that is using the capacity rate method.

[0182] Reference Signs List

[0183] Description of reference numbers used in drawings are defined as follows. First a figure reference number is specified, and then a short name of the item, arrow, flow of information or method step is presented, and in some cases also briefly described. Method steps are marked with a prefix “S” added to a number from S100 to S740.

[0184] 20= A run-around-coil (RAC) platform, which is a heat recovery system that may be a part of a Ventilation Air Conditioning (HVAC) system.

[0185] 21= A run-around coil (RAC) system with sensors to support the Differential Temperature Method (DTM), implemented as a Table method.

[0186] 22= Outdoor air.

[0187] 23= A Run-Around Coil (RAC) system with sensors to support the Capacity Rate Method (CRM), implemented as a Table method.

[0188] 24= Outdoor air stream temperature sensor.

[0189] 26= Heat exchanger for brine to outdoor air stream.

[0190] 28= Heat exchanger for brine to supply air stream.

[0191] 30= Supply air stream temperature sensor.

[0192] 31= Supply air flow sensor, optional at least when using the differential temperature method.

[0193] 32= Supply air fan or pump.

[0194] 34= Supply air.

[0195] 36= Second brine temperature sensor.

[0196] 37= Second brine temperature sensor 36, here integrated in a temperature and flow-controlled valve unit 39.

[0197] 38= Safety valve for avoiding too high pressure in brine circuit

[0198] 39= Temperature and flow-controlled valve unit 39.

[0199] 40= expansion vessel for brine fluid.

[0200] 41= Brine flow circuit.

[0201] 42= Second Three-way valve for brine flow temperature control.

[0202] 43= Brine flow sensor.

[0203] 46= Brine flow pump, or brine flow control actuator.

[0204] 47= Third brine temperature sensor.

[0205] 48= Brine flow heat exchanger, a first.

[0206] 49= Central brine flow temperature sensor.

[0207] 50= Brine flow heat exchanger, a second. 51= Brine flow heat exchanger, with central brine flow circuit.

[0208] 52= Three-way valve for brine flow control over outdoor to supply air flow heat exchangers 26, 28.

[0209] 54= First brine temperature sensor.

[0210] 56= Extract air.

[0211] 58= Heat exchanger for extract air stream to brine.

[0212] 60= Heat exchanger for exhaust air stream to brine.

[0213] 61= Exhaust air flow sensor, optional at least when using the differential temperature method.

[0214] 62= Exhaust air fan or pump.

[0215] 63= Exhaust air temperature sensor.

[0216] 64= Exhaust air.

[0217] 70= Control system for controlling the RAC 20, 21, 23 comprising logics, inputs, outputs, memory, and a computing processor, and / or a hardware implemented control system such as PI or PID regulators.

[0218] 72= Inputs to control system from sensors in the RAC 20.

[0219] 73= Brine flow control signal, an internal signal, or data value in the control system 70, that controls via output 74, the brine flow pump or flow control actuator 46.

[0220] 74= Outputs from control system to actuators in the RAC 20.

[0221] 76= Correction table, providing pre-calculated brine control corrections based on sensor data from temperature sensors, flow sensors, or a combination of temperature and flow sensors in the RAC 20. The correction table can be implemented as a look up function, or even as a basic neural network component.

[0222] 78= Method implementation typically as: software program, circuit connections, field programmable array (FPGA), Kalman based control mechanism, or neural network implementation.

[0223] 80= Diagram presenting temperature efficiency as a function of relative temperature different over coils air / liquid.

[0224] 81= Axis: Temperature efficiency [%].

[0225] 82= Axis: Relative temperature difference over coils air / liquid.

[0226] 83= The curve shows the temperature efficiency as a function of relative temperature difference over brine / liquid side and air side of coils.

[0227] The curve shows how temperature efficiency [%] depends on relative temperature difference over coils air / liquid. A relative value 1 indicates that the temperature difference over the air side and the temperature difference over the brine side are equal. If the brine temperature difference is lower than the air side temperature difference, for example due to a very high brine flow, then the temperature efficiency is lower, as indicated to the right hand of the diagram.

[0228] On the other hand if the brine flow is too low, then the temperature difference over the brine side will increase, and the temperature difference over the air side will be lower, resulting in a lower temperature efficiency [%] as seen on the left hand side of the diagram.

[0229] The diagrams represent tests done on the FlaktGroup product named “EcoNef ’ with the following conclusions: a) The general insight that low flow rates degrade efficiency needs to be revised. b) Liquid flow measurements become uncertain at low flows which affects achieved efficiency for the CRM. c) The differential temperature method is sensitive to low precision of temperature sensors.

[0230] 84= The brine flow is too low for efficient energy transfer. By increasing the brine flow it is expected that the energy transfer efficiency will increase, and that the exhaust air temperature 63 will decrease, until the optimal energy transfer is reached.

[0231] 85= The brine flow is too high for efficient energy transfer. By reducing the brine flow it is expected that the energy transfer efficiency will increase, and that the exhaust air temperature 63 will decrease, until the optimal energy transfer is reached.

[0232] 91= Axis: Temperature efficiency [%].

[0233] 92= Axis: Relative capacity flow rate liquid / air or brine.

[0234] 93= The curve may represent a constant air flow of 1000, 750, 500, 250 [1 / s] or an average curve, showing the temperature efficiency as a function of relative capacity flow rate of brine / liquid side and air side of coils. Optimal efficiency is reached when the relative capacity flow rate of brine liquid and airflow is 1, that is when the capacity flow rate over liquid (brine) is equal to the capacity flow rate over the air flow.

[0235] 95= Table with measured relations between:

[0236] - Supply flow (m3 / h)

[0237] - Exhaust air flow (m3 / h)

[0238] - Relation Supply air to Exhaust air flow

[0239] - Brine temperature (°C) - Outdoor air temperature (°C)

[0240] Method steps are presented as follows:

[0241] SI 00= Method for optimized RAC regulation, implementing the Differential Temperature Method Optimized (DTMO).

[0242] SI 50= Maximizing brine flow to ensure initial energy efficiency.

[0243] S200= Regulating using DTM, CRM, or Table method to control brine flow.

[0244] S210= Regulating using DTM to control brine flow.

[0245] S220= Regulating using CRM to control brine flow.

[0246] S230= Regulating using table method to control brine flow.

[0247] S2320= Correcting brine flow using extra parameters for DT method.

[0248] S2330= Fine tuning using sensor data.

[0249] S2340= Receiving extra sensor data: air exhaust temperature 63.

[0250] S2350= Updating correction table using advanced sensor data.

[0251] S2370= Updating correction table.

[0252] S2380= Updating correction table using advanced sensor data and knowledge, which is using historical sensor data from earlier executions for statistical processing and identification of corrections.

[0253] S240= Regulating using DTM with compensation and correction from Correction Table 76.

[0254] S250= Regulating using CRM with compensation or correction from Correction Table 76.

[0255] S300= Correcting brine flow control signal by optimizing for low exhaust air temperature with iterations using a slow process to control brine flow.

[0256] S310= Testing if preconditions for correcting brine flow are fulfilled.

[0257] S3110= Enable calibration correction when air flow exists.

[0258] S3120= Enable calibration correction when brine flow exists.

[0259] S3130= Enable calibration correction when DTM provides stability in regulation with control error close to zero.

[0260] S3135= Enable calibration correction when CRM method provides stability in regulation with control error close to zero.

[0261] S3140= Cancelling calibration correction when Air flow changes (continuous).

[0262] S3150= Increasing number of Tries until max no is reached; and then reset number of Tries made. S3160= Enable calibration correction when at heat recovery.

[0263] S320= Test a: if feasible to increase brine flow.

[0264] S330= Test b: if feasible to decrease brine flow.

[0265] S340= Identification of best correction and within allowed regulation range based on the number of steps that does not improve optimization.

[0266] S3410= Using max correction effect allowed to introduce inertia in regulation.

[0267] S400= Regulating brine flow.

[0268] S410= Regulating brine flow using the brine flow control signal determined using the differential temperature method (DTM) or capacity rate method (CRM) with correction optimization, with correction data from correction table 76 using: air flow rate, or at a constant air flow rate.

[0269] S4210= Fine tuning of brine flow using offset on pump control.

[0270] S4220= Regulating brine flow extra parameters for DTM or CRM using for example a PID regulator.

[0271] S4230= Fine tuning of sensor data correction data for sensor data processed by the DTM or CRM.

[0272] S4240= Tuning of brine flow using calibration data from zero flow temperature control.

[0273] S500= State transition from S400 Regulating the brine flow; to S300 correcting brine flow by optimizing for low exhaust air temperature 63.

[0274] S600= State transition from S400 Regulating the brine flow; to S200 regulating using DT, CRM, or Table method to control brine flow.

[0275] S610= State transition from S200 regulating using DT, CRM, or Table method to control brine flow; to S400 Regulating the brine flow, without using step S300 correcting brine flow by optimizing for low exhaust air temperature.

[0276] S700= Calibrating sensors by regulating brine flow using the DT method to control brine flow plus calibration data comprising a sensor calibration step; and using sensor calibration correction data in DT method as temperature sensor input.

[0277] S710= Calibrating temperature sensors at air flow from Outdoor Air to Supply Air, with zero brine flow.

[0278] S720= Calibrating temperature sensors at brine from Brine-in to Brine-out, with zero air flow as supply side.

[0279] S730= Identifying and setting calibration for usage in DT, CRM, or Table method.

[0280] S740= Reporting or raising an alarm relating to deviations in heat capacity:

[0281] If large correction needs are indicated in step S710 to S730 then a fault regarding too high or too low glycol percentage may be indicated and reported to a super-visioning system or operator.

Claims

1. A method for controlling an air handling unit (AHU) with a liquid-coupled Run-Around- Coil (RAC) system, comprising(S200) Controlling the brine flow of the RAC (20, 21, 23) by utilizing (S210, S220) a primary control algorithm for temperature efficiency control (83, 93) to tune a brine flow control signal (73) and(S400) Regulating the brine flow (46) using the brine flow control signal (73), wherein the method is characterized in that the method further comprises, when the primary control algorithm is finished tuning the brine flow control signal (73),(S300) Correcting the brine flow through a correcting process by optimizing for a temperature parameter through iterative adjustments using an incremental process to control the brine flow control signal (73).

2. The method according to claim 1, wherein the liquid-coupled Run-Around-Coil (RAC) system is configured as a heat recovery system.

3. The method according to claim 2, wherein the temperature parameter is a lowest exhaust air temperature, and the optimizing for the temperature parameter is to minimize the exhaust air temperature.

4. The method according to claim 2 or 3, wherein the temperature parameter is the temperature difference between the exhaust air temperature and the extract air temperature and the optimizing for the temperature parameter is to optimize towards the highest temperature difference between the extract air temperature and the exhaust air temperature.

5. The method according to any of claim 2 to 4, wherein the temperature parameter is a highest supply air temperature, and the optimizing for the temperature parameter is to maximize the supply air temperature.

6. The method according to any of claim 2 to 5, wherein the temperature parameter is the temperature difference between the supply air temperature and the outdoor air temperature and the optimizing for the temperature parameter is to optimize towards the highest temperature difference between the supply air temperature and the outdoor air temperature.

7. The method according to claim 1, wherein the liquid-coupled Run-Around-Coil (RAC) system is configured as a cooling recovery system.

8. The method according to claim 7, wherein the temperature parameter is a highest exhaust air temperature, and the optimizing for the temperature parameter is to maximize the exhaust air temperature.

9. The method according to claim 7 or 8, wherein the temperature parameter is the temperature difference between the exhaust air temperature and the extract air temperature and the optimizing for the temperature parameter is to optimize towards the highest temperature difference between the exhaust air temperature and the extract air temperature.

10. The method according to any of claim 7 to 9, wherein the temperature parameter is a lowest supply air temperature, and the optimizing for the temperature parameter is to minimize the supply air temperature.

11. The method according to any of claim 7 to 10, wherein the temperature parameter is the temperature difference between the supply air temperature and the outdoor air temperature and the optimizing for the temperature parameter is to optimize towards the highest temperature difference between the outdoor air temperature and the supply air temperature.

12. The method according to any preceding claim, wherein Correcting the brine flow is through correcting the control signal (73).

13. The method according to any preceding claim, wherein Correcting the brine flow is through correcting sensor signals.

14. The method according to any preceding claim, wherein the method further comprises updating the primary control algorithm based on a correction found by the correcting process and again controlling the brine flow of the RAC (20, 21, 23) utilizing (S210, S220) the updated primary control algorithm for temperature efficiency control (83, 93).

15. The method according to any preceding claim, wherein utilizing (S210, S220) the primary control algorithm includes (S210, S240) utilizing a differential temperature method controlling the brine flow control signal (73) for temperature efficiency control (83).

16. The method according to claim 15, wherein utilizing a differential temperature method includes controlling a brine flow control signal (73) for maintaining the differential temperature over an air side and a brine side of coils, respectively, as equal as possible, (54, 36) at 0.8 to 1.4 preferably at 1.0 for temperature efficiency control (83).

17. The method according to claim 15 or 16, wherein utilizing the DTM further comprises regulating the brine flow of the RAC (20, 21, 23) using the DTM by controlling the brine flow of the RAC (20, 21) controlling a valve (52, 42) or by controlling a brine flow pump (46) such that the temperature difference between a supply air stream temperature sensor 30 and an Outdoor air stream temperature sensor (24) reaches the same temperature difference as between the first brine temperature sensor 54 and the second brine temperature sensor (36) whereby the DTM is finished.

18. The method according to any preceding claim, wherein utilizing (S210, S220) the primary control algorithm includes (S220, S250) utilizing a capacity rate method controlling the brine flow control signal (73) for temperature efficiency control (93).

19. The method according to claim 18, wherein utilizing the capacity rate method for temperature efficiency control (93) includes controlling the brine flow control signal (73) for maintaining the capacity flow rate on the air side and brine side of the coils, respectively, as equal as possible (32) (54, 37, 43) at 0.8 to 1.3 preferably at 1.0.

20. The method according to claim 18 or 19, wherein utilizing (S210, S220) the primary control algorithm using the capacity rate method includes controlling the brine flow of the RAC (20, 23) by controlling a valve (52, 42) or by controlling a brine flow pump (46) such that the capacity rate of the supply air stream or extract air stream and the brine flow reaches the same magnitude whereby the CRM is finished.

21. The method according to any preceding claim dependent on claim 15 wherein utilizing (S210, S220) the primary control algorithm further comprises (S240) regulating with compensation or correction from a Correction Table (76), wherein the correction table is configured to translate a temperature difference of the air supply flow, and a temperature difference of the brine flow, into a brine control actuator control signal that controls the brine flow.

22. The method according to any preceding claim dependent on claim 16 wherein utilizing (S210, S220) the primary control algorithm further comprises (S250) regulating with compensation or correction from a Correction Table (76), wherein the correction table is configured to translate a capacity rate of the air supply flow, and a capacity rate of the brine flow, into a brine control actuator control signal that controls the brine flow.

23. The method according to any preceding claim, characterized in that Controlling the brine flow of the RAC S200 utilizing the primary control algorithm further comprises:(S230) Regulating using a table method to control brine flow using correction a table (79) to realize the differential temperature method, or capacity rate method further comprises: (S2310) Correcting brine flow with fine tuning using offset;(S2320) Optionally correcting brine flow using extra parameters for differential temperature method;(S2330) Fine-tuning using sensor data; and(S2340) Receiving extra sensor data: air exhaust temperature24. The method according to claim 23, wherein the method further comprises:(S2370) Updating correction table, where in correction values are improved and updated for improved brine flow control signals for differential temperature parameters, or brine flow control signals (73) for capacity rate parameters.

25. The method according to claim 23 or claim 24, wherein Regulating using a table method to control brine flow using correction a table (79) to realize the differential temperature method, or capacity rate method (S230) further comprises:(S2350) Updating correction table using advanced sensor data;(S2370) Updating correction table; and(S2380) Updating correction table using advanced sensor data and knowledge.

26. The method according to any previous claim, wherein the method further comprises one or more of:(S3110) Enable calibration correction when air flow exists;(S3120) Enable calibration correction when brine flow exists;(S3130) Enable calibration correction when differential temperature method provides stability in regulation with control error close to zero, or(S3135) Enable calibration correction when capacity rate method provides stability in regulation with control error close to zero.

27. The method according to any preceding claim wherein the method further comprises starting the primary control algorithm by maximizing the brine flow control signal (73) for a maximal brine flow, to ensure energy efficiency (SI 50) is preceding Controlling the brine flow of the RAC (20, 21, 23), during start up when sensor parameters are unknown; or as a backup fault handling state.

28. A control system (70) comprising: a processing unit (70), a memory (78) configured to a store control program data (78); an interface to at least one temperature sensor (63, 30) and / or an interface to an air flow sensor; an interface to a brine flow sensor (43); the control system characterized in that the control system is configured to execute the method according to any preceding claim.

29. A run around coil system (20, 21) comprising a control system (70) according to claim 28, wherein the run around coil system comprises: an interface to the control system (70) comprising input signals from sensors (72); at least one outdoor air (22) to supply air (34) flow heat exchanger (26, 28) configured for heat exchange with a brine flow circuit (41); at least one extract air (56) to exhaust air (64) flow heat exchanger (58, 60) configured for heat exchange with the brine flow circuit (41); an exhaust air temperature sensor (63) and / or a supply air temperature sensor (30); andthe brine flow circuit (41) comprises a brine flow pump (46) or at least a valve (42, 52) configured for brine flow control over the at least one of said heat exchangers (26, 28, 58, 60).

Images