Temperature reading-based control electric drive system

Abstract

A method for operating an electric drive system is provided. For example, a controller retrieves from memory a predictive model indicating a predicted winding temperature associated with a known negative temperature coefficient (NTC) temperature, wherein the predictive model is based on historical NTC temperatures and historical winding temperatures, and one or more operating parameters. The controller receives current NTC information indicating one or more current NTC readings corresponding to one or more switching devices within the inverter. The controller determines an estimated winding temperature corresponding to the motor based on the predictive model and one or more current NTC readings and the current operating parameters. The controller provides instructions based on the estimated winding temperature to adjust the motor input.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Provisional Application Serial No. 63 / 021,964, filed May 8, 2020, entitled “CONTROLLING MULTI-PHASE ELECTRIC SYSTEMS BASED ON TEMPERATURE READINGS”, the entire disclosure of which is expressly incorporated herein by reference. Technical Field

[0003] This disclosure generally relates to electric drive systems, and more specifically to techniques for controlling the operation of electric drive systems based on temperature readings. Background Technology

[0004] Electric drive systems (e.g., electric motors) are used in a variety of applications, including electric vehicles. For example, the drive system of an electric vehicle typically includes an alternating current (AC) electric motor driven by a direct current (DC) power source (e.g., a main battery). The AC electric motor is connected to the DC power source via a power inverter that performs a switching function to convert DC power to AC power. An example of an electrical system includes a six-phase motor with six windings.

[0005] In some cases, thermal stress on the windings of an electrical system can cause phase imbalance, which may lead to noise in the system after a period of time. Furthermore, in some examples, the windings can operate within a specific temperature range, and operation outside this range may damage the windings. Embedded temperature sensors within the windings can provide feedback to prevent damage to coil attachments and / or to prevent phase imbalance due to thermal stress. However, some electrical systems may not have embedded winding temperature sensors. Moreover, even if the device has such sensors, they may occasionally malfunction. Therefore, there remains a need to develop techniques to address one or more of the aforementioned shortcomings. Summary of the Invention

[0006] According to one embodiment, this disclosure provides a method for operating an electric drive system including a motor, an inverter, and a controller. The method includes the steps of: the controller retrieving from a memory a prediction model indicating a predicted winding temperature associated with a known thermistor negative temperature coefficient (NTC) temperature, wherein the prediction model is based on historical NTC temperatures and historical winding temperatures; receiving current NTC information indicating one or more current NTC readings corresponding to one or more switching devices within the inverter; determining an estimated winding temperature corresponding to the motor based on the prediction model and the one or more current NTC readings; and providing instructions based on the estimated winding temperature to adjust the input to the motor.

[0007] In some embodiments, the method further includes the steps of: determining the prediction model that indicates the predicted winding temperature associated with the known NTC temperature; and storing the prediction model in the memory.

[0008] In some implementations, the step of determining the prediction model may include the following steps: receiving the historical winding temperatures over a first time period from one or more temperature sensors operatively coupled to one or more windings of the motor; receiving the historical NTC temperatures over the first time period from one or more NTC temperature sensors; and using a dataset to train a model to generate the prediction model using the historical winding temperatures and the historical NTC temperatures.

[0009] In some implementations, the step of training the model may include determining a nonlinear or linear mathematical model using the historical NTC temperatures from all transistors and the historical winding temperatures.

[0010] In some embodiments, the step of determining the prediction model may further include the following steps: adjusting one or more operating parameters associated with the electric drive system; receiving a second historical winding temperature set from one or more temperature sensors operatively coupled to the one or more windings of the motor based on the adjustment of the one or more operating parameters; receiving a second historical NTC temperature set from the one or more NTC temperature sensors based on the adjustment of the one or more operating parameters, wherein the step of using the dataset to train the model to generate the prediction model includes: training the dataset using the historical winding temperatures, the historical NTC temperatures, the second historical winding temperature set, and the second historical NTC temperature set.

[0011] In some implementations, adjusting one or more operating parameters may include adjusting the switching frequency associated with the one or more switching devices within the inverter.

[0012] In some implementations, adjusting one or more operating parameters may include adjusting the direct current (DC) voltage associated with a power source, wherein the power source supplies DC power to the inverter.

[0013] In some implementations, adjusting one or more operating parameters may include adjusting the stator current associated with the inverter and the motor.

[0014] In some implementations, adjusting one or more operating parameters may include adjusting the power factor (PF) associated with the multiphase electrical system.

[0015] In some implementations, adjusting one or more operating parameters may include changing the switching method of the inverter.

[0016] According to another embodiment, this disclosure provides a controller for an electric drive system having a motor and an inverter. The controller includes a processor and a memory storing a plurality of instructions, which, when executed by the processor, cause the controller to: retrieve a prediction model indicating a predicted winding temperature associated with a known thermistor negative temperature coefficient (NTC) temperature, wherein the prediction model is based on historical NTC temperatures and historical winding temperatures; receive current NTC information indicating one or more current NTC readings corresponding to one or more switching devices within the inverter; determine an estimated winding temperature corresponding to the motor based on the prediction model and the one or more current NTC readings; and provide instructions based on the estimated winding temperature to adjust the input to the motor.

[0017] In some implementations, when the multiple instructions are executed, the controller also causes the controller to: determine the prediction model indicating the predicted winding temperature associated with the known NTC temperature; and store the prediction model in the memory.

[0018] In some implementations, determining the prediction model includes: receiving historical winding temperatures over a first time period from one or more temperature sensors operatively coupled to one or more windings of the motor; receiving historical NTC temperatures over the first time period from one or more NTC temperature sensors; and using a dataset to train a model to generate the prediction model using the historical winding temperatures and the historical NTC temperatures.

[0019] In some implementations, training the model includes using the historical NTC temperature and the historical winding temperature to determine a nonlinear or linear mathematical model.

[0020] In some implementations, determining the prediction model includes: adjusting one or more operating parameters associated with the electric drive system; receiving a second historical winding temperature set from one or more temperature sensors operatively coupled to one or more windings of the motor based on the adjustment of the one or more operating parameters; and receiving a second historical NTC temperature set from the one or more NTC temperature sensors based on the adjustment of the one or more operating parameters, wherein training the model using the dataset to generate the prediction model includes: training the dataset using the historical winding temperatures, the historical NTC temperatures, the second historical winding temperature set, and the second historical NTC temperature set.

[0021] In some implementations, adjusting the one or more operating parameters includes adjusting the switching frequency associated with the one or more switching devices within the inverter.

[0022] In some implementations, adjusting the one or more operating parameters includes adjusting the direct current (DC) voltage associated with a power source, wherein the power source supplies DC power to the inverter.

[0023] In some implementations, adjusting the one or more operating parameters includes adjusting the stator current associated with the inverter and the motor.

[0024] In some implementations, adjusting the one or more operating parameters includes adjusting the power factor (PF) associated with the multiphase electrical system.

[0025] In some implementations, adjusting the one or more operating parameters includes changing the switching method of the inverter.

[0026] In some implementations, adjusting the one or more operating parameters includes: adjusting the stator current associated with the inverter and the motor, adjusting the power factor (PF) associated with the multiphase electrical system, or changing the switching method of the inverter.

[0027] In some implementations, when the multiple instructions are executed, the controller also activates derating in the case of high temperature values, based on the estimated motor winding temperature.

[0028] While several embodiments have been disclosed, other embodiments of the subject matter will become apparent to those skilled in the art from the following detailed description illustrating and describing exemplary embodiments of the disclosed subject matter. Therefore, the accompanying drawings and detailed description should be considered illustrative in nature and not restrictive. Attached Figure Description

[0029] The above and other features and advantages of this disclosure, as well as the ways in which they are obtained, will become clearer and the invention itself will be better understood by referring to the following description of embodiments of the invention in conjunction with the accompanying drawings, in which:

[0030] Figure 1 This is a block diagram illustrating a six-phase electric drive system;

[0031] Figure 2 This is an example Figure 1 Block diagram of the controller and six-phase inverter of a six-phase electrical system;

[0032] Figure 3 This is an example Figure 1 A block diagram of the controller and six-phase electrical equipment of a six-phase electrical system;

[0033] Figure 4 This is an example operation. Figure 1 A flowchart of a method for a six-phase electrical system; and

[0034] Figure 5 It is a graphical representation of the relationship between the temperature of a negative temperature coefficient (NTC) temperature sensor and the temperature of the motor windings.

[0035] Throughout these views, corresponding labels indicate the corresponding parts. The examples described herein illustrate exemplary embodiments of this disclosure, and these examples should not be construed as limiting the scope of this disclosure in any way. Detailed Implementation

[0036] To facilitate understanding of the principles of this disclosure, reference is now made to the following embodiments illustrated in the accompanying drawings. The exemplary embodiments disclosed herein are not intended to be exhaustive or to limit this disclosure to the precise forms disclosed in the following detailed description. Rather, these exemplary embodiments have been chosen and described so that others skilled in the art may utilize their teachings.

[0037] The terms “connected,” “connected,” and variations thereof are used to include both an arrangement in which two or more components are in direct physical contact and an arrangement in which two or more components are not in direct contact with each other (e.g., these components are “connected” via at least a third component) but still cooperate or interact with each other.

[0038] Throughout this disclosure and in the claims, numerical terms such as first and second are used to refer to various components or features. This use is not intended to indicate an order of these components or features. Rather, numerical terms are used to help the reader identify the referenced components or features and should not be interpreted narrowly as providing a specific order of components or features.

[0039] Those skilled in the art will recognize that the provided implementations can be implemented in hardware, software, firmware, and / or a combination thereof. The programming code according to the implementations can be implemented in any feasible programming language, such as C, C++, HTML, XTML, JAVA, or any other feasible high-level programming language, or a combination of high-level and low-level programming languages.

[0040] As described below, a method and / or system for estimating motor winding temperature using a negative temperature coefficient (NTC) temperature sensor is defined. The estimation of the winding temperature may have a non-linear relationship with the NTC temperature. Thus, a data-driven method and system are proposed to determine this relationship. For example, the winding temperature can be sensed for different operating conditions / parameters. Simultaneously, the NTC temperature is also sensed. Therefore, the relationship between the NTC temperature and the winding temperature can be estimated while taking operating conditions into account.

[0041] Now refer to Figure 1 A block diagram of a six-phase electrical system 100 is shown, which includes a six-phase motor 102, an inverter 104, a controller 106 (e.g., a supervisory control module (SCM)), and a power supply 108. The controller 106 controls the operation of the six-phase motor 102 via the inverter 104, such that the six-phase motor 102 can use DC power input supplied to the inverter 104 by the power supply 108. As used herein, the term "motor" refers to an AC-powered device and / or machine that converts electrical energy into mechanical energy or mechanical energy into electrical energy. These electrical devices can be categorized as synchronous motors and asynchronous motors. Synchronous motors can include permanent magnet motors and reluctance motors. In some cases, the six-phase motor 102 is a six-phase asymmetric permanent magnet synchronous motor used to provide torque in electric vehicles. However, it should be understood that the disclosed embodiments may relate to other types of electrical systems in the context of other applications.

[0042] The six-phase motor 102 has six windings 102A to 102F, each winding being associated with a corresponding phase A to F of the six-phase motor 102. Windings 102A to 102C are connected together at a first neutral connection 110, while windings 102D to 102F are connected together at a second neutral connection 112. The first neutral connection 110 and the second neutral connection 112 are electrically isolated. With this configuration, the six-phase motor 102 is mounted as if it were two separate three-phase motors. That is, windings 102A to 102C comprise the first set of three phases, while windings 102D to 102F comprise the second set of three phases. These two sets of windings are shifted (e.g., spatially) by 30° of electrical phase value relative to each other to improve torque performance.

[0043] Windings 102A to 102F represent the stator of the six-phase motor 102. For ease of illustration, the stator and other components (e.g., rotor, shaft, etc.) of the six-phase motor 102 are not shown. Typically, the rotor is mounted to the shaft, and the rotor is separated from the stator by an air gap. When used as a motor, the stator uses electrical energy to rotate the rotor, which in turn rotates the shaft to provide mechanical energy. On the other hand, when used as a generator, external mechanical force rotates the shaft, which in turn rotates the rotor, thereby generating electrical energy in the stator.

[0044] The six-phase inverter 104 particularly includes switching devices (e.g., transistors and / or diodes) to properly switch the DC voltage and provide excitation to the windings 102A to 102F of the six-phase motor 102, as known to those skilled in the art. In some examples, the inverter 104 may be a pulse-width modulation inverter.

[0045] The controller 106 can receive information such as temperature readings (e.g., temperature readings of a negative temperature coefficient (NTC) thermistor) from the inverter 104. The controller 106 can also control the operation of the inverter 104. For example, the controller 106 can provide instructions to the inverter 104 to adjust the switching frequency and / or switching method of the inverter 104. The inverter 104 will be described in more detail below.

[0046] Power source 108 can be any type of DC power source, such as a battery (e.g., a vehicle battery). Power source 108 supplies DC power to six-phase inverter 104 via power lines 120A and 120B. For example, controller 106 can control the amount of power (e.g., voltage and / or current) supplied by power source 108 to six-phase motor 102 via six-phase inverter 104.

[0047] Controller 106 (e.g., SCM) controls the operation of six-phase electrical system 100. For example, controller 106 includes a motor winding temperature determination (MWTD) unit 116 and a memory 118. Controller 106 (e.g., MWTD unit 116) receives information from six-phase motor 102 and / or other sensors / devices within six-phase electrical system 100. This information may include voltage information (e.g., DC voltage from power supply 108), current information (e.g., current from inverter 104 to six-phase motor 102), temperature information (e.g., NTC temperature information and / or winding temperature information), and / or other types of information. Controller 106 retrieves information from memory 118, such as a predictive model relating winding temperature and NTC TS readings. Controller 106 uses the predictive model and / or the received information to determine one or more estimated winding temperatures for windings 102A to 102F. Controller 106 adjusts the inputs (e.g., current / voltage) to motor 102 based on the estimated winding temperatures. This will be described in more detail below.

[0048] In some variations, memory 118 is a non-transitory memory with instructions that, in response to execution by a processor (e.g., controller 106), enable the processor to control the operation of the electrically driven system 100 (e.g., execute method 400). The processor, non-transitory memory, and controller 106 are not particularly limited and may, for example, be physically separate.

[0049] In some embodiments, controller 106 may form part of a processing subsystem that includes one or more computing devices having memory, processing, and communication hardware. Controller 106 may be a single device or a distributed device, and the functionality of controller 106 may be executed by hardware and / or as computer instructions on a non-transitory computer-readable storage medium (e.g., non-transitory memory). In some embodiments, controller 106 includes one or more interpreters, determiners, evaluators, regulators, and / or processors that functionally perform the operations of controller 106. The interpreters, determiners, evaluators, regulators, and processors may implement computer instructions in hardware and / or as non-transitory computer-readable storage media, and may be distributed across various hardware or computer-based components.

[0050] Figure 2 A more detailed block diagram of the inputs, outputs, connections, and / or components of a six-phase inverter 104 in a six-phase electrical system 100 is shown. For example, the six-phase inverter 104 includes six switching modules 202A through 202F. Each module may contain two switching devices. Each switching device 202A is electrically connected to the windings of the six-phase motor 102 (e.g., 102A through 102F). Additionally, the switching devices 202A through 202F also include negative temperature coefficient temperature sensors (NTC TS) 204A through 204F. The NTC TS 204A through 204F determine, monitor, and / or detect the temperature of the switching devices 202A through 202F. The NTC TS 204A through 204F provide information to the controller 106 indicating the temperature readings of the switching devices 202A through 202F. NTC TS 204A to 204F are known in the art and can be any type of temperature sensor that uses a negative temperature coefficient to determine the temperature of switching devices 202A to 202F.

[0051] For example, in some examples, switching devices 202A to 202F are made of transistors (e.g., insulated-gate bipolar transistors (IGBTs)). NTC TS 204A to 204F are NTC thermistors used to determine the temperature of switching devices 202A to 202F. NTC TS 204A to 204F provide sensor information indicating the temperature of switching devices 202A to 202F to controller 106. For example, the resistance of the NTC thermistor changes with temperature. Based on the determined resistance value, controller 106 determines the temperature of the IGBT.

[0052] The six-phase inverter 104 receives inputs 120A and 120B (e.g., power, current, and / or voltage) from a power supply 108. Inputs 120A and 120B can be DC inputs (e.g., DC voltage / current). A voltage sensor 206 is operatively coupled to inputs 120A and 120B and detects the DC voltage supplied to the six-phase inverter 104 by the power supply 108. The voltage sensor 206 provides information indicating the DC voltage to the controller 106.

[0053] The six-phase inverter 104 provides an output of 114A to 114F (e.g., AC current / voltage) to the six-phase electrical equipment 102. In other words, the six-phase inverter 104 provides stator currents of 114A to 114F to the corresponding windings 102A to 102F. The current sensor 208 determines the stator currents of 114A to 114F and provides the sensor information indicating the current to the controller 106.

[0054] Figure 3 A more detailed block diagram of the inputs, outputs, connections, and / or components of the six-phase motor 102 of the six-phase electrical system 100 is shown. For example, stator currents 114A to 114F are supplied to windings 102A to 102F. Windings 102A to 102F use current to generate power. In some examples, windings 102A to 102F include winding temperature sensors (winding TS) 302A to 302F. Winding TS 302A to 302F detect, monitor, and / or determine the temperature at windings 102A to 102F. Winding TS 302A to 302F provide information indicating temperature readings to controller 106.

[0055] Figure 4 A method 400 for operating an electric drive system, such as a six-phase electrical system 100, is shown. Method 400 will refer to the above. Figures 1 to 3 The six-phase electrical system 100 shown is described herein. However, in some examples, method 400 may also be used with other types of electric drive systems, including three-phase electrical systems. Additionally and / or alternatively, method 400 may also be used to power electric vehicles and / or other types of applications.

[0056] In block 402, controller 106 retrieves a prediction model from memory (e.g., memory 118) capable of predicting winding temperatures based on known negative temperature coefficient (NTC) temperatures. This prediction model is based on historical NTC temperatures (transistor temperatures) and historical winding temperatures. For example, controller 106 receives historical NTC temperatures from NTCs TS 204A to 204F. Historical NTC temperatures are the temperatures of switching devices 202A to 202F during a previous time period. Controller 106 also receives historical winding temperatures from windings TS 302A to 302F. Historical winding temperatures are the temperatures of windings 102A to 102F during a previous time period.

[0057] Controller 106 uses historical winding temperatures and historical NTC temperatures from a previous time period (e.g., a first time period) to determine a predictive model. This predictive model indicates an empirical model, relationship, correlation, algorithm, and / or other connection between the historical winding temperatures and the historical NTC temperatures. For example, the predictive model can be a mathematical algorithm, such as a transfer function, higher-order equations, logarithmic equations, and / or any other type of linear / nonlinear equation, or a lookup table. Controller 106 stores the predictive model (e.g., relationships, correlations, algorithms, and / or other connections) in memory 118 and retrieves it in later time periods.

[0058] In other words, controller 106 uses data to train and determine a predictive model (e.g., a mathematical relationship between two temperatures, such as an empirical model). For example, during a previous time period, such as during the development, testing, or calibration phase of the six-phase electrical system 100, controller 106 may operate the six-phase electrical system 100 to determine a predictive model. In other words, during that previous time period, the six-phase motor 102 may include windings TS 302A to 302F. Controller 106 may receive information indicating the temperature of switching devices 202A to 202F using NTC TS 204A to 204F and the temperature of windings 102A to 102F using windings TS 302A to 302F over a period of time. Controller 106 then uses the dataset to train / determine / calculate an empirical model, such as a mathematical relationship (e.g., a nonlinear mathematical model) between two temperature readings from temperature sensors 204A to 204F and 302A to 302F. The controller 106 stores the empirical model in the memory 118, and at a later time, the controller 106 retrieves the empirical model (i.e., the prediction model) from the memory 118.

[0059] Figure 5 A graphical representation of the NTC temperature and winding temperature during a previous time period (e.g., during the testing phase) is shown. For example, controller 106 receives winding temperature 502 from windings TS 302A to 302F. Controller 106 receives NTC temperature 504 from NTCs TS 204A to 204F. Controller 106 uses winding temperature 502 and NTC temperature 504 to determine an empirical model.

[0060] In some variations, the predictive model considers one or more operating parameters of the six-phase electrical system 100. Operating parameters include, but are not limited to, DC voltage (Vdc), switching frequency of switching devices 202A to 202F, power factor (PF), stator currents 114A to 114F, and / or switching method. For example, operating parameters may affect the relationship between the temperatures of switching devices 202A to 202F and the temperatures of windings 102A to 102F. During the data training phase, the controller 106 may consider operating parameters when determining the predictive model.

[0061] In other words, controller 106 can set one or more first operating parameters (e.g., a first switching frequency) for the six-phase electrical system 100, and can collect (e.g., receive) winding temperature information and NTC temperature information under the first operating parameters. Controller 106 can then adjust the operating parameters (e.g., set the switching frequency to a second switching frequency) and can continue collecting winding temperature information and NTC temperature information under the new operating parameters. This process can be repeated, and controller 106 can receive multiple datasets of winding temperature information and NTC temperature information under different operating parameters. Controller 106 can use datasets with different operating parameters to determine a predictive model / empirical model.

[0062] For example, the switching frequency indicates the rate at which switching devices 202A to 202F are turned on or off. In other words, the switching frequency is the rate or frequency at which the DC voltage from DC power supply 108 is turned on and supplies current (e.g., 114A to 114F) to the corresponding windings (e.g., 102A to 102F) or is turned off and no current is supplied to the windings. The switching frequency may affect the NTC temperature reading but may not affect the winding temperature reading. For example, if the switching frequency increases and other operating parameters remain substantially the same, the NTC temperature may increase while the winding temperature may remain the same. Controller 106 can determine the relationship based on a dataset of temperature information at different switching frequencies. Controller 106 can then determine a predictive model / empirical model based on these datasets from different switching frequencies (e.g., by considering the relationship between different switching frequencies and temperature information).

[0063] Vdc is the DC voltage from power supply 108 to inverter 104. Controller 106 receives Vdc from voltage sensor 206. Vdc can affect NTC temperature readings and winding temperature readings by acting in a constant manner or by increasing the slope of the thermal profile. For example, a higher Vdc leads to higher losses in the power switch, resulting in a higher NTC temperature. On the other hand, Vdc has little effect on motor winding losses and temperature. Furthermore, for similar loads, a lower DC voltage may require a higher current from the motor. As a result, the loss and temperature profiles will change accordingly.

[0064] The stator current 114A to 114F is the current from inverter 104 to six-phase electrical equipment 102. Controller 106 receives the stator current 114A to 114F from current sensor 208. The stator current 114A to 114F can affect the NTC temperature reading and winding temperature reading. For example, a higher current will result in higher losses in both the power switches and the motor windings, thus leading to higher temperatures in both the NTC and the motor windings.

[0065] The power factor is the ratio between the real power used to perform work (e.g., to supply a load) and the virtual power circulating in system 100. Controller 106 can set the power factor based on the load applied to system 100 (e.g., operating an electric vehicle). The power factor has little effect on both the NTC and motor winding temperature.

[0066] It should be understood that different switching methods can lead to different losses in the power switch, while the changes in motor winding losses may not be significant. For example, discontinuous pulse width modulation (PWM) results in fewer losses in the power switch compared to continuous PWM, thus leading to lower NTC temperatures.

[0067] In some examples, controller 106 may use a first electric drive system to determine a predictive model and may retrieve or apply that predictive model to a second electric drive system. For example, a six-phase motor 102 for the first electric drive system may include windings TS 302A to 302F. Controller 106 may use the windings TS 302A to 302F from the first electric drive system and NTC TS 204A to 204F from the six-phase inverter 104 to determine the predictive model. The six-phase motor 102 for the second electric drive system may not include windings TS 302A to 302F. Controller 106 may use the predictive model stored in memory 118 to control a second electric drive system that does not include windings TS 302A to 302F. In some cases, the first electric drive system and the second electric drive system are different systems. In other cases, the first electric drive system and the second electric drive system are the same system, and after determining the predictive model, windings TS 302A to 302F are removed from the system.

[0068] In block 404, controller 106 receives NTC temperature information indicating one or more current NTC temperature readings corresponding to one or more power switches 202A to 202F within inverter 104. Controller 106 may receive NTC temperature information from one or more NTC TS 204A to 204F. For example, controller 106 receives the current NTC temperature from NTC TS 204A to 204F after retrieving predictive information based on historical NTC temperatures and historical winding temperatures.

[0069] In block 406, controller 106 determines the estimated winding temperature corresponding to motor 102 based on a predictive model and one or more current NTC temperature readings. For example, in a subsequent time period after the predictive model is determined, controller 106 receives current NTC temperature readings. For example, in system 100 having windings TS 302A to 302F, one or more of windings TS 302A to 302F may have a fault and / or malfunction (e.g., providing inaccurate coil winding temperature readings). Thus, controller 106 can use the predictive model (e.g., an empirical model) determined above to determine the estimated winding temperature.

[0070] Additionally and / or alternatively, the predictive model may indicate a dataset of temperature information (e.g., NTC temperature and / or winding temperature) under different operating parameters. Controller 106 may receive information indicating the current operating parameters of the six-phase electrical system 100 (e.g., current Vdc, current switching frequency of switching devices 202A to 202F, current power factor (PF), current stator currents 114A to 114F, and / or current switching method). Controller 106 may use the current operating parameters and the dataset of temperature information under different operating parameters to determine the estimated winding temperature.

[0071] In other words, the prediction model can include datasets under different operating parameters. Using the current operating parameters, the controller 106 can determine datasets with historical operating parameters similar to the current operating parameters (e.g., if the current Vdc is 10 volts, the controller 106 can determine datasets with historical operating parameters of 10 volts or close to 10 volts (e.g., 8 volts)).

[0072] In some examples, controller 106 adjusts the empirical model based on datasets under different operating parameters and the current operating parameters. For instance, controller 106 can use datasets under different operating parameters to determine whether the switching frequency affects the NTC temperature reading and not the winding temperature reading. Controller 106 adjusts the empirical model based on this information. Then, using the current operating parameters / current switching frequency, controller 106 determines the estimated winding temperature of motor 102.

[0073] In some cases, controller 106 uses a first electric drive system with windings TS 302A to 302F to determine the predictive model. In blocks 404 and 406, controller 106 determines the estimated winding temperature of a second electric drive system. The second electric drive system may not include windings TS 302A to 302F (e.g., the first and second systems are separate systems, and / or, windings TS 302A to 302F are removed after the predictive model is determined). In other words, even if the second electric drive system does not include a winding temperature sensor, controller 106 can still determine the estimated winding temperature and use it to control the system.

[0074] At block 408, controller 106 provides instructions to adjust the input of a motor (e.g., a six-phase motor 102) based on an estimated winding temperature. The input to motor 102 can be any input that can change the winding temperature of windings 102A through 102F. For example, inputs include, but are not limited to, Vdc, switching frequency, switching method, stator current, and / or power factor. For instance, based on determining that the estimated winding temperature is above or below a certain threshold, controller 106 can provide instructions to power supply 108 to adjust Vdc.

[0075] By using the methods and / or systems described above, winding temperature readings can be achieved more quickly. For example, using method 400 to determine winding temperature readings can achieve this faster than receiving temperature readings from windings TS 302A to 302F. Additionally and / or alternatively, costs can be minimized if windings TS 302A to 302F are not required. Furthermore, the methods and / or systems described above allow for greater control flexibility (minimum loss) and / or better predictability during the Analysis-Driven Design (ALD) phase. Moreover, the methods and / or systems described above can support the main controller in triggering any protection mechanisms in case of potential errors in ADC or sensor calibration.

[0076] While the invention has been described with exemplary design, further modifications can be made to the invention within the spirit and scope of this disclosure. Therefore, this application is intended to cover any variations, uses, and alterations of the invention utilizing its general principles. Furthermore, this application is intended to cover deviations from this disclosure that fall within the known or customary practice of the field to which this invention pertains and fall within the limitations of the appended claims.

[0077] Furthermore, the connecting lines shown in the various figures included herein are intended to represent exemplary functional relationships and / or physical connections between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in a practical system. However, any benefit, advantage, or solution to a problem may arise or become more significant, and no element may be considered a critical, essential, or fundamental feature or element. Therefore, the scope is not limited by anything other than the appended claims, wherein, unless expressly stated otherwise, reference to an element in the singular does not mean "one and only one," but rather "one or more."

[0078] Furthermore, when a phrase similar to "at least one of A, B or C" is used in a claim, it is intended to be interpreted as meaning that in an embodiment A may be present alone, in an embodiment B may be present alone, in an embodiment C may be present alone, or in a single embodiment any combination of elements A, B or C may be present; for example, A and B, A and C, B and C, or A and B and C.

[0079] This document provides systems, methods, and apparatus. In the detailed description herein, references to "one embodiment," "an embodiment," "an example embodiment," etc., indicate that the described embodiment may include a particular feature, structure, or characteristic, but each embodiment may not necessarily include that particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when a particular feature, structure, or characteristic is described in conjunction with an embodiment, it implies that it is within the knowledge of those skilled in the art to implement such a feature, structure, or characteristic having the benefits of this disclosure in conjunction with other embodiments, whether explicitly described or not. After reading this description, those skilled in the art should understand how this disclosure can be implemented in alternative embodiments.

[0080] Furthermore, elements, components, or method steps in this disclosure are not intended to be made public, whether or not they are expressly stated in the claims. As used herein, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements does not include only those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Claims

1. A method of operating an electric drive system comprising a motor, an inverter, and a controller, the method comprising the following steps: The controller retrieves from memory a prediction model indicating a predicted winding temperature associated with a known thermistor negative temperature coefficient (NTC) temperature, wherein the prediction model is based on historical NTC temperatures and historical winding temperatures. Receive current NTC information indicating multiple current NTC readings, each current NTC reading corresponding to a switching device within the inverter measured using an NTC thermistor, the NTC thermistor being connected to the switching device, the inverter including multiple switching devices connected to the corresponding multiple NTC thermistors, and each of the multiple switching devices being connected to a corresponding winding among multiple windings of the motor. The estimated winding temperature corresponding to the motor is determined based on the prediction model and the multiple current NTC readings; and Instructions are provided based on the estimated winding temperature to adjust the input of the motor.

2. The method according to claim 1, further comprising the following steps: Determine the prediction model that indicates the predicted winding temperature associated with the known NTC temperature; and The prediction model is stored in the memory.

3. The method according to claim 2, wherein, The steps for determining the prediction model include the following: The historical winding temperature during a first time period is received from multiple winding temperature sensors, each winding temperature sensor being operatively connected to a corresponding winding among the multiple windings of the motor. Receive the historical NTC temperature during the first time period from the plurality of NTC thermistors; and The dataset is used to train the model to generate the prediction model using the historical winding temperature and the historical NTC temperature.

4. The method according to claim 3, wherein, The steps for training the model include: using the historical NTC temperature and the historical winding temperature to determine a nonlinear or linear mathematical model.

5. The method according to claim 3, wherein, The step of determining the prediction model further includes the following steps: Adjust one or more operating parameters associated with the electric drive system; Based on the adjustment of one or more operating parameters, a second historical winding temperature set is received from the winding temperature sensor; Based on adjustments to one or more operating parameters, a second set of historical NTC temperatures is received from the plurality of NTC thermistors, and The step of using a dataset to train a model to generate the prediction model includes: using the historical winding temperature, the historical NTC temperature, the second historical winding temperature set, and the second historical NTC temperature set to train the dataset.

6. The method according to claim 5, wherein, The steps for adjusting one or more operating parameters include adjusting at least one of the following: (1) The switching frequency associated with the plurality of switching devices within the inverter, (2) A DC voltage associated with a power source, wherein the power source provides DC power to the inverter. (3) The stator current associated with the inverter and the motor, and (4) Power factor PF associated with multiphase electrical systems.

7. The method according to claim 5, wherein, The steps for adjusting one or more operating parameters include: changing the switching method of the inverter.

8. The method according to claim 1, wherein, Based on the estimated motor winding temperature, the controller activates derating at high temperature values.

9. A controller for an electric drive system having a motor and an inverter, the controller comprising: processor; as well as A memory storing a plurality of instructions, which, when executed by the processor, cause the controller to perform the method according to any one of claims 1 to 8.

10. An electric drive system, the electric drive system comprising: Electric motor; Inverter; A power supply configured to provide DC power to the inverter; as well as The controller according to claim 9 is operatively connected to the motor, the inverter and the power supply.

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