The technical field generally relates to controllers, and more particularly to methods and systems for controlling a temperature of a controller processor.
Controllers control the operation of one or more components of a system. For example, vehicle controllers control one or more components of a vehicle via associated actuators. Generally, a vehicle controller includes a control program that includes instructions that are performed by a processor for controlling the operation of the component. In some instances, the processor of the controller may overheat due to overuse or environmental conditions. Overheating of the processor may shorten the processor's lifetime and can cause computations performed by the processor to be unreliable.
Accordingly, it is desirable to provide methods and systems for controlling a temperature of a controller processor. It is further desirable to provide methods and systems to configurably control a temperature of a controller processor. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.
Methods and systems are provided for controlling a temperature of a processor of a controller. In one embodiment, a method includes: collecting a first set of measurement data based on measurement parameters; processing the first set of measurement data associated with the processor using a predictor model to determine a temperature of the processor; and selectively controlling the temperature of the processor based on the determined temperature.
In one embodiment, a system includes a non-transitory computer readable medium. The non-transitory computer readable medium includes a first module that collects a first set of measurement data based on measurement parameters. The non-transitory computer readable medium further includes a second module that processes the first set of measurement data associated with the processor using a predictor model to determine a temperature of the processor. The non-transitory computer readable medium further includes a third module that selectively controls the temperature of the processor based on the determined temperature.
The exemplary embodiments will hereinafter be described in conjunction with the following drawing figures, wherein like numerals denote like elements, and wherein:
The following detailed description is merely exemplary in nature and is not intended to limit the application and uses. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. As used herein, the term module refers to any hardware, software, firmware, electronic control component, processing logic, and/or processor device, individually or in any combination, including without limitation: application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
Embodiments may be described herein in terms of functional and/or logical block components and various processing steps. It should be appreciated that such block components may be realized by any number of hardware, software, and/or firmware components configured to perform the specified functions. For example, an embodiment may employ various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices. In addition, those skilled in the art will appreciate that embodiments may be practiced in conjunction with any number of control systems, and that the vehicle system described herein is merely one example embodiment.
For the sake of brevity, conventional techniques related to signal processing, data transmission, signaling, control, and other functional aspects of the systems (and the individual operating components of the systems) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and/or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in various embodiments.
With reference now to
As shown, the vehicle 12 includes a controller 14. The controller 14 controls one or more components 16a-16n of the vehicle 12. The controller 14 includes at least one processor 18, memory 20, one or more input and/or output (I/O) devices 22, one or more sensing devices 28, and one or more cooling devices 30. The I/O devices 22 communicate with one or more sensors and/or actuators associated with the components 16a-16n of the vehicle12 to control the components 16a-16n. The sensing devices 28 sense observable conditions associated with the processor 18 and generate sensor signals based thereon. The cooling devices 30 are controlled to cool the processor 18, for example, by fan or other means.
The memory 20 stores instructions that can be performed by the processor 16. The instructions stored in memory 20 may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. In the example of
When the controller 14 is in operation, the processor 18 is configured to execute the instructions stored within the memory 20, to communicate data to and from the memory 20, and to generally control operations of the vehicle 12 pursuant to the instructions. The processor 18 can be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the controller 14, a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, or generally any device for executing instructions.
In various embodiments, the processor 18 executes the instructions of the temperature control system 10. The temperature control system 10 generally monitors and collects data measured by the sensing device(s) 28. The temperature control system 10 processes the data to predict a temperature of the processor 18 and/or a rate of change of temperature associated with the processor 18. The temperature control system 10 controls the temperature of the processor 18 based on the predicted temperature and/or rate of change of temperature.
Referring now to
The monitoring module 32 collects and stores measurement data to support the prediction of the temperature and the control of the temperature. The measurement data is stored in a history datastore 38. For example, as shown in greater detail in
In various embodiments, the history datastore 38 includes a circular buffer 44. The size of the circular buffer 44 and the format of data structures stored in each can be configured. In such embodiments, the monitoring module 32 tracks an index associated with the circular buffer 44. For example, after receiving the measurement data 40 and formatting the measurement data 40 into a data structure, the monitoring module 32 stores the data structure in the circular buffer 44 at allocation associated with the index and then increments the index to the next write position in the circular buffer 44. Once the index reaches the last location in the circular buffer 44, the monitoring module 32 sets the index to the index value associated with the first location. In this manner, once the circular buffer 44 is full, the oldest data is overwritten first.
In another example, after receiving a request 46 to receive data from the history datastore 38, the monitoring module 32 retrieves the data structures associated with the indexes between: index-1 and (index-1)-count, where the count is assumed to be less than the buffer size. The count can be configurable, for example based on the predictor model used by the predictor module 34 (as will be described in more detail below).
In various embodiments, how the data is collected and what data is collected by the monitoring module 32 is configurable. For example, the monitoring module 32 may receive measurement parameters 48 from the predictor module 34 (i.e., based on the predictor model used for the prediction) at 54; and the monitoring module 32 generates a request for the data 50 based on the parameters 48 at 52. The monitoring module 32 further formats the measurement data 40 at 42 based on the measurement parameters 48. For example, the measurement parameters 48 may include, but are not limited to, an indication of direct measurement by way of the temperature sensor, an indication of indirect measurement by way of task level or hardware level sensing (e.g., instruction cycles, cache miss/hit, etc.), uniform sampling, and/or non-uniform sampling.
With reference back to
For example, the temperature of the processor 18 typically depends on two factors: processor thermal characteristics related to heat transfer and materials (fixed), and application thermal characteristics related to instructions per time unit, memory access, I/O access, etc. The predictor module 34 receives and evaluates current measurement data 40 to select which predictor model to execute.
The predictor module 34 selects the predictor model 62 that would be best suitable for prediction based on the conditions indicated by the current measurement data 40. For example, the predictor module 34 includes a table 66 with structures such as: <current_temperature, current_workload, sensing_state, measure_conf>. The predictor module 34 evaluates the table 66 to decide which predictor model 62 to use and the corresponding measurement parameters 48 to use to measure the data (e.g., current_temp and current_workload from measurement). In various embodiments, the predictor module 34 determines the predictor model 62 to be used based on a current sensing state 68 associated with system services (e.g. diagnostic, indicating availability of sensing devices).
The selected predictor model 62 is then executed by the predictor module 34. The predictor model 62 requests measurements from the monitoring module 32 via the request for data 46 based on the measurement parameters 48. The predictor module 34 then processes the received measurement data 40 using the selected predictor model 62 to generate the predicted temperature and/or the rate of change of the temperature 70. Example predictor models 62 can include, but are not limited to, regressive moving average for uniform temperature measurement:
T
t
=e
t−1+Σqi=1(ciet−i)−Σpi=1(aiTt−i), and (1)
a band limited temperature frequency uniform workload, non-uniform temperature measurement:
With reference back to
For example, as shown in more detail in
With reference now to
In various embodiments, the method may begin at 105. The measurement data 40 is received at 110. The measurement data 40 is evaluated by the predictor module 34 to determine the predictor model 62 and the measurement parameters 48120. The measurement data 40 is collected based on the measurement parameters 48 and the request for data 46 at 130. The collected measurement data 40 is evaluated using the selected predictor model 62 to determine the temperature and/or the rate of change in temperature 70 at 140. The action policy is determined based on the measurement data 40 and the temperature and/or rate of change in temperature 70 at 150. The control signals 80 are generated to carry out the action(s) of the action policy at 160. Thereafter, the method may end at 170.
While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the exemplary embodiment or exemplary embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the disclosure as set forth in the appended claims and the legal equivalents thereof.