Patent Description:
There are various technical limitations that prevent achievement of inflight optimization. The current technology often misses accurate flight plan information (e.g., downlink messages contain limited amount of information). In addition, current flight management systems do not support real-time weather such as 3D Grid weather, and the size of wind/temperature uplink messages is limited, thus resulting in inaccuracies of the onboard weather model. Also, a lack of systems connectivity prevents effective responses to unforeseen weather changes along the route, and datalink costs resulting from onboard weather updates can be prohibitive.

<CIT> discloses a system comprising a dynamic transmission process and a processor unit. The processor unit is configured to run the dynamic transmission process. The dynamic transmission process is configured to receive environmental information. The dynamic transmission process determines whether to send the environmental information to a subscriber.

The present invention in its various aspects is as set out in the appended claims. A system and method for improving vehicle efficiency in terms of fuel saving and/or time accuracy through onboard weather update is provided. The system comprises a processor, and a non-transitory processor readable medium including instructions, executable by the processor, to perform a method comprising: receiving weather data related to a vehicle traveling from an origin location to a destination location from an onboard vehicle data source; receiving real-time weather data from one or more weather data sources; detecting when onboard forecast weather data is different than the real-time weather data based on the weather data related to the vehicle for at least one segment of a plurality of segments of a vehicle travel path, wherein a segment comprises a climb, cruise, or descent segment ; determining, based on the real-time weather data and the weather data related to the vehicle, a weather error for each of the at least one segment of a plurality of segments of the vehicle travel path; determining an error threshold for each of the at least one segment of a plurality of segments of the vehicle travel path, wherein if the weather error for a given flight segment of the at least one segment of a plurality of segments of the vehicle travel path is greater than a corresponding error threshold for the given flight segment, then: estimating based on the real-time weather data and the weather data related to the vehicle, one or more potential benefits in terms of fuel saving and/or time accuracy from an update of the onboard forecast weather data; and activating the update of the onboard forecast weather data to the given flight segment; and updating when the one or more potential benefits is above a predefined threshold, the onboard forecast weather data to the real-time weather data for the at least one segment of a plurality of segments of the vehicle travel path.

In the following detailed description, embodiments are described in sufficient detail to enable those skilled in the art to practice the invention.

A system and method of enhancing vehicle efficiency through smart automation for onboard weather updates are disclosed herein. The system and method provide functionality that allows smart and optimized combinations of real-time vehicle data, such as flight plan data, with live weather data, such as 4Dimensional Meteorological (4DM) data, 3D Grid weather (Wx) data, crowd sourced weather data, or connected weather data, in order to estimate benefits that could result from updates of the onboard forecast weather data. If beneficial, the onboard weather forecast data can then be updated, either automatically or by a user such as a vehicle crew member or ground dispatcher.

The present system and method can be implemented for various vehicles, including airborne vehicles such as various types of aircraft, such as manned aircraft, unmanned aerial vehicles (UAVs), and the like, as well as ground-based vehicles such as cars, trucks, and the like.

In one implementation, the present approach provides up-to-date weather data for enhancing inflight efficiency of aircraft by combining real-time aircraft flight plan data (e.g., lateral and vertical routes, time schedules, and onboard weather data) with live weather data, such as 4DM data, 3D Grid Wx data, crowd sourced weather data, or connected weather data, in order to detect when onboard forecast weather is either out-of-date or irrelevant. The benefits that could result from updates of the onboard weather data are then estimated, which can be in terms of fuel saving and/or time accuracy, for example. For dispatchers, this information can be provided for all aircrafts under his/her responsibility, with dedicated cues to display the benefits, and highlights when medium/high benefits can be achieved.

The user is then allowed to update onboard weather data through automatic or manual generation and uplink of relevant information, such as predicted wind information (PWI) messages, predicted wind modification (PWM) messages, or the like. Alternatively, the user can update onboard weather data through automatic or manual generation and upload of relevant weather data to an electronic flight bag (EFB) application, enabling compressed/reduced data size. The EFB application can then use the up-to-date weather data to: generate PWI/PWM messages, or the like; allow the pilot to view these data (and eventually modify the data); and if allowed by the onboard technology, send the PWI/PWM messages to a flight management system (FMS). Otherwise, manual pilot entry of the updated data is needed.

The present method can also be implemented to automatically perform the update of the onboard weather data whenever benefits are higher than a user-defined threshold. In addition, the method also allows for restricting the weather update to specific flight segments where most of the benefits are evaluated.

Logic used to implement the present method can be located in a FMS, EFB, ground server, the cloud, or the like.

The present approach provides various benefits, including: enhanced inflight efficiency of an aircraft, through determination of real-time cost efficient speeds and altitudes, as well as calculation of a cost-efficient descent profile for the aircraft; improved on-time performance as accuracy of the forecast weather allows accurate and reliable time predictions; reductions in crew and dispatcher workloads; reduced datalink costs through optimization of weather data exchanges, as only required and useful data will be uplinked; and flight rerouting capabilities.

The present method can also be implemented to provide up-to-date weather data to onboard systems hosting an optimum speed/altitude engine (e.g., EFB, FMS, or the like). Having accurate weather data in the FMS, for example, can provide additional benefits by ensuring accurate fuel predictions (hence crew confidence) and accurate time predictions.

Further details of the present system and method are described hereafter with reference to the drawings.

<FIG> and <FIG> are general diagrammatic representations of a system <NUM> for enhanced efficiency through smart automation for an onboard weather update, according to an exemplary implementation. The system <NUM> is generally implemented using real-time flight plan data from an aircraft <NUM>, and up-to-date weather (Wx) data from a ground source <NUM>. This information is used by system <NUM> to detect when onboard forecast weather data is out-of-date or irrelevant, and to estimate the potential benefits of updating the onboard forecast weather data. The system <NUM> then selects relevant weather data along the flight plan for the update, and provides compression of the weather data update as needed. An automatic uplink of the weather data update is then sent to aircraft <NUM>. <FIG> illustrates that system <NUM> can be operated through an FMS <NUM>, an EFB application <NUM>, or both, onboard aircraft <NUM>. Alternatively, system <NUM> can be operated using an on-ground or cloud computing service.

<FIG> is a flow diagram of an exemplary operational method <NUM> for enhancing vehicle efficiency, such as flight efficiency. The method <NUM> can be operated as part of an onboard service, or as part of an on-ground or cloud service.

Initially, method <NUM> refreshes predictions and weather (block <NUM>) based on a flight plan and predictions, sent from an onboard vehicle data source such as a FMS or EFB (either cyclically or through a push manually) (block <NUM>), and live weather data such as 3D grid weather data (block <NUM>). The method <NUM> then performs optimization (OPT) profile research (block <NUM>) to determine whether onboard forecast data is out-of-date or irrelevant. A benefit detection is then performed (block <NUM>) to estimate the potential benefits of updating the onboard forecast weather data, based on one or more applied thresholds (e.g., airline, custom, variable) (block <NUM>).

A determination is then made whether to apply customization manually or automatically (block <NUM>). If manual customization is applied, then the benefit is visualized (block <NUM>) such as on a user display, and the user is allowed to validate the benefit (block <NUM>). If automatic customization is applied, then benefit validation take places without any user input (block <NUM>). A determination is made whether the benefit is valid, either manually or automatically (block <NUM>). If the benefit is not valid, method <NUM> comes to an end (block <NUM>). If the benefit is determined to be valid, weather and optimization updates are selected (block <NUM>), and sent to the onboard FMS or EFB. An onboard display then shows a benefits and optimization proposal (block <NUM>), which can then be automatically or manually activated (block <NUM>).

<FIG> is a block diagram showing further details of an exemplary scheme <NUM> for detecting when onboard weather data is out-of-date or irrelevant. As shown, onboard inputs (block <NUM>), such as from an FMS or EFB, and ground inputs (block <NUM>) are utilized for scheme <NUM>. The onboard inputs include weather data of an optimum speed and altitude engine, an optimum descent profile engine, and a time predictions engine, for example. The ground inputs include live weather data, such as live 3D Grid weather data. The onboard inputs and ground inputs are used in the determination of weather error, Wx_error (e.g., wind and temperature), for each given flight segment i (e.g., climb, cruise, descent) (block <NUM>). For example, if the weather error is greater than a wind error threshold for a given segment (if Wx_error_i > wind_err_threshold_i), then the method goes on to the next step of estimating benefits, such as fuel and time benefits, along that segment. Otherwise, the method displays cues associated with no benefit along the given segment. (block <NUM>).

<FIG> is a block diagram showing further details of an exemplary scheme <NUM> for estimating the benefits that could result from updates of the onboard weather data. The estimation of benefits can be in terms of fuel saving and/or time accuracy, and accounts for updated optimum speed/altitudes, for example. As shown, onboard inputs including a real-time active flight plan (block <NUM>), and ground inputs of live 3D Grid weather data (block <NUM>), are utilized for scheme <NUM>. The onboard inputs and ground inputs are used in the execution of the following engines, along the active flight plan (or any secondary flight plans) and with the 3D Grid weather data: if segment_i < descent: optimum speed and altitude engine; if segment_i = descent: optimum descent profile engine; and the time predictions engine (block <NUM>). The savings of the estimated benefits compared to the current flight plan is then displayed to the user for the different flight segments (climb, cruise, descent) (block <NUM>).

The user (crew or dispatcher) is allowed to update the onboard weather data. For example, the user can generate and upload weather data associated to each individual flight segment (climb/cruise/descent) (blocks <NUM>). The user can also generate and upload weather data along the complete flight plan (block <NUM>). The user can additionally update the optimum speeds/altitudes (block <NUM>).

In one example embodiment, color determination can be employed as part of the display for the user. For example, a GREEN message color can indicate a low savings cost compared to the transaction cost; an AMBER message color can indicate a medium savings cost; a WHITE message color can indicate information is already updated; and a RED message color can indicate that the user should update the data because of high benefits.

The present method also provides for smart selection of relevant weather data surrounding a real-time flight plan (vertical and lateral trajectories) to produce an accurate weather model. For climb and descent flight segments, the method selects altitudes based on relevant weather points (e.g., wind direction change, wind magnitude change, tropopause altitude, etc.) to allow accurate 2D modelization of actual weather. For cruise flight segments, the method selects altitudes and waypoints based on relevant weather points such as wind points, and optimizes updates with respect to planned steps. Elapsed time to reach the weather points is also considered.

An example of the determination of relevant wind points for a climb segment is shown in the graph of <FIG>. The relative wind points are automatically analyzed with respect to a vertical profile and a headwind profile (Wx grid), between an origin and T/C. The graph of <FIG> can be used to perform an automatic selection of flight levels of interest by a fitting algorithm. For example, based on a delta change of wind/temperature, a maximum delta between two flight levels can be determined.

A processor used in the present system can be implemented using software, firmware, hardware, or any appropriate combination thereof, as known to one of skill in the art. These may be supplemented by, or incorporated in, specially-designed application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). The computer or processor can also include functions with software programs, firmware, or other computer readable instructions for carrying out various process tasks, calculations, and control functions used in the present system.

The present methods can be implemented by computer executable instructions, such as program modules or components, which are executed by at least one processor. Generally, program modules include routines, programs, objects, data components, data structures, algorithms, and the like, which perform particular tasks or implement particular abstract data types.

Instructions for carrying out the various process tasks, calculations, and generation of other data used in the operation of the methods described herein can be implemented in software, firmware, or other computer- or processor-readable instructions. Various process tasks can include controlling spatial scanning and orientation, laser operation, photodetector control and operation, and awareness of system orientation and state. These instructions are typically stored on any appropriate computer program product that includes a computer readable medium used for storage of computer readable instructions or data structures. Such a computer readable medium can be any available media that can be accessed by a general purpose or special purpose computer or processor, or any programmable logic device.

Claim 1:
A system (<NUM>) for improving vehicle efficiency in terms of fuel saving and/or time accuracy through onboard weather update, the system (<NUM>) comprising:
a processor; and
a non-transitory processor readable medium including instructions, executable by the processor, to perform a method comprising:
receiving weather data related to a vehicle traveling from an origin location to a destination location from an onboard vehicle data source;
receiving real-time weather data from one or more weather data sources;
detecting when onboard forecast weather data is different than the real-time weather data (<NUM>) based on the weather data related to the vehicle for at least one segment of a plurality of segments of a vehicle travel path, wherein a segment comprises a climb, cruise, or descent segment;
determining, based on the real-time weather data and the weather data related to the vehicle (<NUM>), a weather error for each of the at least one segment of a plurality of segments of the vehicle travel path;
determining an error threshold for each of the at least one segment of a plurality of segments of the vehicle travel path, wherein if the weather error for a given flight segment of the at least one segment of a plurality of segments of the vehicle travel path is greater than a corresponding error threshold for the given flight segment, then:
estimating based on the real-time weather data and the weather data related to the vehicle (<NUM>), one or more potential benefits in terms of fuel saving and/or time accuracy from an update of the onboard forecast weather data to the given flight segment; and
updating when the one or more potential benefits is above a predefined threshold, the onboard forecast weather data to the real-time weather data for the at least one segment of a plurality of segments of the vehicle travel path