Systems and methods for monitoring energy efficiency of the drive systems

The subject-matter disclosed herein relates to systems and methods for monitoring energy efficiency of at least one drive system, in particular of at least one electromechanical drive system.

The sub ect-matter disclosed herein also relates to a computer program comprising instructions for carrying out the above-mentioned method and to a computer-readable medium comprising such computer program.

When referred to "drives" herein, it is referred to variablefrequency drives (VFDs) that are known as frequency converter, adjustable-frequency drives (AFDs) , adjustable-speed drives (ASDs) , variable-speed drives (VSDs) , AC drives, micro drives, inverter drives or, simply, drives.

Within the scope of the present disclosure, the drive system is a drive and an electric machine, e.g., a motor such as a three-phase motor, e.g., an asynchronous motor. The drive directly supplies the electrical machine in the context of electrical drive technology. Frequency and amplitude can be derived from the operating state of the electrical machine.

Sustainability is getting more and more importance in our society and a legislation is accordingly updated that impacts on energy related products. Different sustainability goals are set that apply not only to energy consumption and savings but also in C02 emissions and material economy. Electric drive systems are fully affected from these activities as energy related products.

Especially, for energy efficiency monitoring purposes it is often required to install external cost intensive sensors for power and energy consumption determination concerning the high frequency spectrum that is introduced from the frequency converter .

Energy consumption and sustainability relevant KPI s monitoring is for sure the first step to establish a green footprint . However, due to the limited energy resources worldwide the minimi zation of the power consumption as well as the saving potential that state-of-the-art products can achieve and indicate on the end application is an added value . As well as a recommendation system to operate the existing drive in a more ef ficient way .

The goal of the present disclosure is to provide a system to monitor energy ef ficiency of one or more drive systems in a real-time .

The goal is achieved by a system the system comprising a memory that stores machine-executable components , a processor that is operatively coupled to the memory, and is configured to execute the machine-executable components , and an interface that is configured to query and receive and/or collect real-time sensor data from a drive of the at least one drive system, wherein the sensor data is based on measurements performed by sensors comprised by the drive and is representative of an operational state of the at least one drive system . The machine-executable components comprise a drive system analyzer component configured to receive the sensor data via the interface , executing an energy ef ficiency model on the sensor data to calculate at least one energy ef ficiency relevant key performance indicator (KPI ) of the at least one drive system provide the at least one energy ef ficiency relevant KPI of the at least one drive system .

The sensor data is collected by the sensors that are already present within the drive and not by some external sensors and/or hardware devices. This is very advantageous, since each external sensor increase the costs, but also the energy consumption and the CO2 footprint of the monitoring system.

In an embodiment, the interface is configured to query the sensor data with an interface-specific sampling frequency, e.g., 100 milliseconds. "Interface-specific" means that the sampling is performed with a maximum sampling frequency, which can be achieved by using this particular interface. This usually depends on hardware of the interface.

In an embodiment the interface comprises one or more data busses .

In an embodiment, the drive system analyzer component is configured to aggregate the sensor data for a predetermined time period, e.g., for five minutes.

In an embodiment, the real-time sensor data comprises torque, rotational speed, frequency (output frequency of the drive) , actual current (RMS current) , rated drive current, rated drive supply voltage, power factor (cos cp) , DC link voltage.

In an embodiment, said executing energy efficiency model comprises determining at least one of mechanical power of an electric machine of the at least one drive system, utilization degree of the drive (converter utilization degree) , power loss of the drive, power loss of a reference drive.

The description of the reference drive and its losses can be acquired from a standard or another norm. In particular this information is acquired from a standard set by the IEC (International Electrotechnical Commission) , e.g., from the standard IEC61800-9-2. In an embodiment , said executing energy ef ficiency model further comprises determining at least one of based on the mechanical power of an electric machine of the at least one drive system, a power loss of the electric machine , based on the power loss of the drive , a power consumption of the at least one drive system, based on the power loss of the drive and the power loss of the reference drive , a power losses ratio in the drive and/or power savings due to/achieved by using the drive , when compared to using the reference drive .

In an embodiment , said executing energy ef ficiency model further comprises determining at least one of based on the power savings , saved energy resulting from using the drive system compared to using the reference drive , based on the power consumption of the at least one drive system, an energy consumption of the at least one drive system .

In an embodiment , said executing energy ef ficiency model further comprises determining at least one of based on the saved energy, costs and/or CO2 savings for the at least one drive system, based on the energy consumption of the drive system, operation costs for the at least one drive system and/or CO2 emissions/ footprint produced by the at least one drive system .

In an embodiment , the energy ef ficiency relevant KPI is from the group : power loss of the drive , power loss of a reference drive , power loss of an electric machine of the at least one drive system, utili zation degree of the drive , power consumption of the drive , energy consumption of the at least one drive system, operating costs , CO2 equivalent emission, power losses ratio , power savings , energy savings , CO2 savings , cost savings . In an embodiment , the system further comprises a user interface configured to receive user commands to configure the drive system analyzer component to determine , which sensor data is to be queried/collected by the interface from the drive of the at least one drive system and/or the energy ef ficiency model .

Configuring the drive system analyzer component in this case may also involve configuring the interface via the drive system analyzer component . In an embodiment , the interface may comprise a data collector, which can be designed as a software component and can be configurable via a ( first ) user interface that can be directly connected to the data collector .

In an embodiment , the machine-executable components comprise a recommendation component configured to , based on the at least one energy ef ficiency relevant KPI of the at least one drive system, a) to propose an eco- friendly operation setting for the drive / frequency converter, and/or b) to propose actions for bypassing or shutting down the drive / frequency converter to reduce consumption of resources , and/or c) to indicate energy savings in case of installing of a more energy ef ficient electric machine ( e . g . , IE5 PEM motor, SynRM motor etc . ) and/or more energy ef ficient drive/ frequency converter and/or a drive/ frequency converter with regenerative capability .

Proposing an eco- friendly operation setting may include but not limited to , based on one or more KPI s , change in switching frequency of the drive , propose control techniques that aim on motor magnetic flux optimi zation, propose a selection of proper pulse modulator, especially in the overmodulation area . In an embodiment, the machine-executable components comprise a visualization component configured to, based on the at least one energy efficiency relevant KPI, provide at least one signal to visualize the at least one energy efficiency relevant KPI .

In an embodiment, the at least one signal is designed to be visualized in form of at least one widget.

In an embodiment, the signal comprises at least the information regarding the power losses ratio KPI, and the widget comprises a region to visualize a current efficiency mode, which is defined based on preset limit values (in percent) for the power losses ratio KPI.

In an embodiment, the region is designed as circle that can be colored green, if the power losses ratio is less or equal than a first preset limit value, yellow, if the power losses ratio is larger than the first preset limit value and is less or equal than a second preset limit value, and red, if the power losses ratio is larger than the second preset limit value .

The goal is also achieved by a computer-aided method for monitoring energy efficiency of at least one drive system, in particular of at least one electro-mechanical drive system, the method comprising: querying, e.g., via or by the interface, and receiving, e.g., at the drive system analyzer, real-time sensor data from a drive of the at least one drive system, wherein the sensor data is based on measurements performed by sensors comprised by the drive and is representative of an operational state of the at least one drive system, executing, e.g., at the drive system analyzer, an energy efficiency model on the sensor data to calculate at least one energy efficiency relevant key performance indicator (KPI) of the at least one drive system, providing, e.g., at the interface or at a user interface, the at least one energy efficiency relevant KPI of the at least one drive system.

In an embodiment, the method further comprises configuring the energy efficiency model.

In an embodiment, the method further comprises configuring the drive system analyzer component to determine, which sensor data is to be queried/collected by the interface from the drive of the at least one drive system.

In an embodiment, the method further comprises, based on the at least one energy efficiency relevant KPI of the at least one drive system, a) proposing an eco-friendly operation setting for the drive / frequency converter, and/or b) proposing actions for bypassing or shutting down the drive / frequency converter in order to reduce/save resources, and/ or c) indicating energy savings in case of a installing of a more energy efficient electric machine (e.g., IE5 PEM motor, SynRM motor etc.) and/or more energy efficient drive/ frequency converter and/or a drive/ frequency converter with regenerative capability.

The above and other aspects and advantages of the subject matter disclosed herein will be further discussed in conjunction with the accompanying drawings, which indicate only some possible ways that may be practiced. The like reference characters in the drawings refer to like parts throughout.

FIG 1 shows an example of an OT infrastructure,

FIG 2 shows KPI visualization in form of widgets, and

FIG 3 shows an energy efficiency model. FIG 1 shows an exemplified OT (operational technology) infrastructure for implementing the subject-matter disclosed herein .

The infrastructure comprises a plurality (1, 2, 3, 4, N) of drive systems and at least one industrial PC (personal computer) IPC.

It will be appreciated by those skilled in the art that the industrial PC can be exchanged by any on-prem and/or cloud computing device.

Each drive system comprises a drive unit AU1, AUN, e.g., a frequency converter that drives an electric machine, e.g., an electric motor.

The industrial PC IPC can be designed as an edge device comprising one or more ports, data busses DBUS, data connectors CC, interfaces, e.g., user interfaces UI1, UI2, UI2, etc.

In particular, the industrial PC IPC comprises a data collector DCA, which can be designed as a software program, such as application .

The data collector app DCA is configured to query and/or collect real-time sensor data from the plurality of the drives AU1, ..., AUN of the corresponding drive systems.

In an embodiment, the data collector DCA may have several different data connectors DCONN, e.g., HF, LF (for high/low frequency) connector, a fingerprint connector, etc. to query specific data from the drives AU1, ..., AUN. The configuration of the data connectors DCONN can be provided by API (application programming interface) .

The sensor data is based on measurements performed by sensors comprised by the corresponding drive AU1, ..., AUN and is representative of an operational state of the at least one drive system. In particular the data is relevant for determining energy efficiency of the at least one drive system.

For example, the sensor data can comprise torque T, rotational speed n, frequency f (output frequency of the drive) , actual current I (RMS current) , rated drive current I _N , rated drive supply voltage U _N , power factor (cos of phi) , DC link voltage U.

Further data can be provided to or queried by the data collector DCA. In an embodiment, the machine-readable product designation of each drive AU1, ..., AUN, nominal grid frequency, etc.

In an embodiment, the raw data, e.g., in form of time series is provided / queried continuously.

The data collector DCA can comprise a first user interface UI1 that is configured to receive user commands to configure, which sensor data is to be collected and/or with which sampling frequency. The sampling frequency is data-collector- specific. In an embodiment, the sampling frequency depends on hardware properties of a data bus that is used by the industrial PC IPC to collect/query the data from the drives AU1, ..., AUN.

In an embodiment, a user U can be connected to the first user interface UI1 via Internet, e.g., by using an http protocol.

The data collector app DCA passes the data (the raw data) for further data handling DH. In an embodiment, an MQTT protocol is used to communicate between the data collector DCA and the data handling level DH. The data handling DH can be performed over a data bus DBUS, which can be connected to one or more connectors CC, e.g., a cloud connector, e.g., via http, PLCs, e.g. , via MQTT etc. In an embodiment, the data bus DBUS can be connected to a second user interface UI2 configured to receive user commands for data routing. E.g., it can be configured to forward part of raw data to a cloud service, e.g., for model training, etc. In an embodiment, a user U can be connected to the second user interface UI2 via Internet, e.g., by using the http protocol .

The data handling module DH can provide resources for various further data services or for an information hub.

Via the data bus DBUS the sensor data is forwarded to a drive system analyzer DSA. MQTT communication protocol can be used here as well. In an embodiment, the drive system analyzer is a software component. In an embodiment, the drive system analyzer DSA can be designed as an app, e.g., an edge app .

In an embodiment, the drive system analyzer DSA can comprise a data aggregation module DAM configured to buffer a predetermined amount of data. In an embodiment, the data aggregation module is configured to buffer the sensor data for five minutes. By choosing an appropriate sampling frequency enough of sensor data can be aggregated in five minutes to produce a single data point.

The drive system analyzer DSA provides an environment for executing one or more models - a runtime, e.g., in Python programming language. For example, the drive system analyzer DSA can comprise a model for condition estimation CE of the drive and/or of the electric machine, e.g., of a motor.

To estimate the energy efficiency of each drive system the drive system analyzer DSA comprises an executable energy efficiency model EEM.

In an embodiment, the drive system analyzer DSA can comprise a database DB, which stores various models, configurations, results of previous analysis by various models etc. The energy efficiency model EEM is designed to receive the (aggregated) sensor data and to calculate at least one energy efficiency relevant key performance indicator (KPI) of the corresponding drive system.

The drive system analyzer DSA and its modules, e.g., the data aggregation module DAM, the energy efficiency model EEM, etc. can be configured via a third user interface UI3.

The third user interface UI3 can be also used to provide the KPIs to the user U. The user U can configure the model and adjust its settings with the aid of the third user interface UI3. E.g., the user U may set price per kWh, emitted CO2 per kWh, set mains frequency and/or voltage, etc. This can be useful for a visualization of the energy efficiency.

In an embodiment, the energy efficiency relevant KPI is from the group: power loss of the drive, power loss of a reference drive, power loss of an electric machine of the at least one drive system, utilization degree of the drive, power consumption of the drive, energy consumption of the at least one drive system, operating costs, CO2 equivalent emission, power losses ratio, power savings, energy savings, CO2 savings, cost savings.

In an embodiment, the at least one KPI can be forwarded to the cloud service for further analysis or to train Al models.

In an embodiment, the KPI or KPIs can be forwarded to the user U via the third user interface UI3 for monitoring purposes and/or further analysis.

In an embodiment, the drive system analyzer DSA comprises a visualization component configured to, based on the at least one energy efficiency relevant KPI, provide at least one signal to visualize the at least one energy efficiency relevant KPI. This signal can be sent to the user's U display device UD.

In an embodiment, the user U can access the first, the second and the third user interfaces by using a computing device, e.g., via http. This means that the user U does not have to be physically present at the place of employment of the drive systems and can be somewhere else.

In an embodiment, the user U can configure the energy efficiency model EEM - adjust its settings.

In an embodiment, the drive system analyzer DSA can comprise an application programming interface API that allows for configuration of the drive system analyzer DSA. In an embodiment, it allows to configure energy efficiency model EEM (and other models) , and/or data handling within the drive system analyzer DSA, e.g., data aggregation, providing the energy efficiency KPIs, visualization, etc.

In an embodiment, the drive system analyzer DSA can comprise a recommendation component. The recommendation component is configured to receive one or more energy efficiency relevant KPI of the at least one drive system as an input and, based on the KPI value, to propose an eco-friendly operation setting for the frequency converter.

In an embodiment, the recommendation component is configured to propose actions for bypassing or shutting down the frequency converter to reduce/save resources.

In an embodiment the recommendation component is configured to indicate energy savings in case of a new installation of the most efficiency product (e.g., IE5 PEM motor, SynRM motor etc . ) The signal for visualization of one or more KPIs can be sent to user's U computation device and visualized on its display UD.

FIG 2 illustrates examples of two widgets that can be provided via the display device UD to the user U. The widgets regard to different industrial applications and show daily power consumption in kW over the time. The efficiency mode of the corresponding drive system can be specified, e.g., by a colored circle. In an embodiment, the circle can be colored green, yellow or red, depending on the efficiency of the operating mode.

In an embodiment, the widgets provide information about daily development of the KPIs (energy consumption, CO2 emission, cost) as well as their historical behavior.

Turning to FIG 3 an example of a calculation of the energy efficiency KPIs by the energy efficiency model EEM is presented as a flowchart.

As discussed above, the energy efficiency model EEM can receive torque T, rotation speed n, RMS value of the current I, rated current I _N , machine-readable product designation MLFB, output frequency of the drive f, power factor cos (cp) , and rated line supply voltage U _N .

The energy efficiency model EEM can be preconfigured by the user U. In particular the user U can be asked to input line voltage, C02 emission factor, electricity price, etc.

Based on the input sensor data and on the user' s configuration, the energy efficiency model can determine at first one or more of mechanical power of the motor of the corresponding drive system, utilization degree of the drive (converter utilization degree) , power loss of the drive , power loss of a reference drive .

In an embodiment , the energy ef ficiency model can determine power loss of the corresponding motor based on the mechanical power of the motor .

In an embodiment , the energy ef ficiency model can determine power consumption of each drive system based on the power loss of the drive .

In an embodiment , the energy ef ficiency model can determine power losses ratio in the drive and/or power savings due to/achieved by using the drive , when compared to using the reference drive , based on the power loss of the drive and the power loss of the reference drive .

In an embodiment , based on the power losses ratio .

In an embodiment , the energy ef ficiency model can determine saved energy resulting from using the drive in the drive system compared to using the reference drive , based on the power savings .

In an embodiment , the energy ef ficiency model can determine energy consumption of each drive system, based on the power consumption of the drive system .

In an embodiment , the energy ef ficiency model can determine costs and/or CO2 savings for each drive system, based on the saved energy .

In an embodiment , the energy ef ficiency model can determine operation costs for the at least one drive system and/or CO2 emissions/ footprint produced by the at least one drive system, based on the energy consumption of the drive system . The above-described embodiments of the present disclosure are presented for purposes of illustration and not of limitation . In particular, the embodiments described with regard to figures are only few examples of the embodiments described in the introductory part . Technical features that are described with regard to systems can be applied to augment methods disclosed herein and vi ce versa .