Electric vehicle pre-conditioning

A method of prompting an operator of an electric vehicle for pre-conditioning the electric vehicle comprises monitoring a location of the electric vehicle, monitoring the temperature of an electric propulsion system within the electric vehicle, accessing historical data of driving patterns for the electric vehicle, monitoring the location of the operator of the electric vehicle, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, comparing the temperature of the electric propulsion system of the electric vehicle to a pre-determined preferred operating temperature, and sending a prompt to the operator of the electric vehicle suggesting that pre-conditioning of the electric vehicle may be appropriate.

INTRODUCTION

The present disclosure relates to a system and method of providing a prompt to the operator of an electric vehicle allowing the operator to initiate pre-conditioning of the electric vehicle.

Electric vehicles are powered by electric motors that run on electricity stored in rechargeable lithium-ion or Nickel Metal Hydride Batteries. One disadvantage of electrical batteries is that batteries are less efficient and provide less power when they are cold. Automobiles are likely to encounter varying temperatures depending on where and how they are used. It is possible, and even likely, that an electric vehicle will be used in a climate where temperatures are cold. Operation of an electric vehicle in temperatures that are less than optimal means the batteries will operate less efficiently. The vehicle electrical requirements do not change in cold temperatures, and in fact, may increase in cold temperatures due to increased HVAC loads. Therefore, when an electric vehicle is operated in very cold temperatures, particularly when first started, when the power output of the batteries and the life of the battery is negatively affected.

To combat this, systems have been developed to warm the batteries before use. In this way, when the electric vehicle is put into use, the batteries are already warm and operate at peak efficiency and power output. In many instances, systems include capability to allow the operator of an electric vehicle to initiate pre-conditioning of the electric vehicle by warming the batteries ahead of time. A key fob, similar to a remote starter device for an internal combustion engine vehicle, may be used to allow the operator of an electric vehicle to initiate pre-conditioning prior to usage of the electric vehicle.

Existing systems depend on foresight of the operator to predict when usage of the electric vehicle is imminent and initiate pre-conditioning of the electric vehicle. Thus, while current systems achieve their intended purpose, there is a need for an improved system that automatically predicts when usage of the electric vehicle may be imminent and provides a prompt to the operator of the vehicle to initiate pre-conditioning.

SUMMARY

According to several aspects, of the present disclosure, a method of prompting an operator of an electric vehicle for pre-conditioning the electric vehicle, comprises monitoring a location of the electric vehicle, monitoring the temperature of an electric propulsion system within the electric vehicle, accessing historical data of driving patterns for the electric vehicle, monitoring the location of the operator of the electric vehicle, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, comparing the temperature of the electric propulsion system of the electric vehicle to a pre-determined preferred operating temperature, and sending a prompt to the operator of the electric vehicle suggesting that pre-conditioning of the electric vehicle may be appropriate.

According to another aspect of the present disclosure, monitoring the location of the operator of the electric vehicle, further includes accessing a personal device belonging to the operator of the vehicle, and using GPS capability within the personal device to monitor the location of the operator of the electric vehicle.

According to another aspect of the present disclosure, a personal device belonging to the operator of the vehicle, and using GPS capability within the personal device to monitor the location of the operator of the electric vehicle, further includes accessing one of an operator's cell phone, smart phone, tablet, laptop computer, and smart watch.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes monitoring the arrival of the electric vehicle at a public transportation hub, monitoring movement of the operator of the electric vehicle from the public transportation hub to at least one location distant from the public transportation hub, while the electric vehicle remains located at the public transportation hub, and monitoring the return of the operator of the electric vehicle to the public transportation hub.

According to another aspect of the present disclosure, monitoring the arrival of the electric vehicle at a public transportation hub, includes monitoring the arrival of the electric vehicle at one of an airport, a bus depot, a train station, car rental agency, and a cruise ship dock.

According to another aspect of the present disclosure, the method further includes accessing the operator's personal device and identifying travel plans from the operator's personal calendar or uploaded itineraries, and monitoring the return of the operator of the electric vehicle to the public transportation hub further includes predicting the return of the operator of the electric vehicle to the public transportation hub based on data from the operator's personal calendar and uploaded itineraries.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes monitoring movement of the electric vehicle to a destination, accessing the operator's personal device, identifying travel plans from the operator's personal calendar or uploaded itineraries, and predicting how long the operator of the electric vehicle will remain at the destination based on data from the operator's personal calendar and uploaded itineraries.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes prompting the operator of the electric vehicle for planned departure time, receiving input from the operator of the vehicle of the planned departure time, and predicting how long the operator of the electric vehicle will remain at the destination based on the planned departure time received from the driver of the electric vehicle.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes monitoring movement of the electric vehicle to a destination, identifying the destination, and predicting how long the operator of the electric vehicle will remain at the destination.

According to another aspect of the present disclosure, predicting how long the operator of the electric vehicle will remain at the destination further includes accessing historical data, identifying past instances where the electric vehicle and the operator traveled to the destination, calculating an average time that the operator spends at the destination, and predicting how long the operator of the electric vehicle will remain at the destination based on the average time the operator of the electric vehicle spends at the destination.

According to another aspect of the present disclosure, predicting how long the operator of the electric vehicle will remain at the destination further includes accessing information from the internet, identifying the nature of the activity at the destination, calculating an average length of time for the identified activity to conclude based on data from the internet, and predicting how long the operator of the electric vehicle will remain at the destination based on the average length of time for the identified activity to conclude.

According to another aspect of the present disclosure, predicting how long the operator of the electric vehicle will remain at the destination further includes accessing the operator's personal device, monitoring financial transactions and electronic payments made by the operator using the personal device, identifying a payment made at the destination, and predicting how long the operator of the electric vehicle will remain at the destination based on identifying a payment made by the operator at the destination.

According to another aspect of the present disclosure, predicting how long the operator of the electric vehicle will remain at the destination further includes detecting when the electric vehicle is plugged in at a charging station, monitoring when charging of the electric vehicle stops, and predicting how long the operator of the electric vehicle will remain at the charging station based on charging of the electric vehicle stopping.

According to another aspect of the present disclosure, predicting how long the operator of the electric vehicle will remain at the destination further includes detecting when the electric vehicle is parked at a public parking facility, accessing a parking application on the operator's personal device, monitoring when a pre-paid parking time will expire, and predicting how long the operator of the electric vehicle will remain at the charging station based on pending expiration of the pre-paid parking time.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes accessing the operator's personal device, identifying recurring planned departures from the operator's personal calendar, and predicting future departures based on data from the operator's personal calendar.

According to another aspect of the present disclosure, identifying a condition that indicates imminent usage of the electric vehicle based on the location of the vehicle, the location of the operator of the electric vehicle, and the historical data of driving patterns for the electric vehicle, further includes identifying patterns of past recurring departures from the historical data, and predicting future departures based on patterns of recurring past departures.

According to several aspects of the present disclosure, a system for providing a pre-conditioning prompt to an operator of an electric vehicle comprises a controller in communication with the electric vehicle and the operator of the electric vehicle, an operator interface adapted to allow the operator of the electric vehicle to communicate with the controller, the controller adapted to track the position of the electric vehicle, track the position of the operator of the electric vehicle, access historical data, access weather information, and send a prompt to the operator of the electric vehicle when the controller identifies conditions indicating use of the electric vehicle is imminent and the temperature where the electric vehicle is located necessitates pre-conditioning of an electric propulsion system within the electric vehicle.

According to another aspect of the present disclosure, the controller communicates with a personal device belonging to the operator of the vehicle, and uses GPS capability within the personal device to monitor the location of the operator of the electric vehicle and send a prompt to the operator of the electric vehicle when the controller identifies conditions indicating use of the electric vehicle is imminent and the temperature where the electric vehicle is located necessitates pre-conditioning of an electric propulsion system within the electric vehicle.

According to another aspect of the present disclosure, the operator interface is integral to the personal device, further wherein the operator of the electric vehicle communicates with the controller and responds to prompts from the controller through the operator interface of the personal device.

According to another aspect of the present disclosure, the personal device is one of an operator's cell phone, smart phone, tablet, laptop computer, and smart watch.

According to another aspect of the present disclosure, the controller is further adapted to communicate with the internet via a cellular network, further wherein the controller is adapted to access information from the internet to identify the nature of an activity at a destination, calculate an average length of time for the identified activity to conclude based on data from the internet, and predict how long the operator of the electric vehicle will remain at the destination based on the average length of time for the identified activity to conclude.

According to another aspect of the present disclosure, the controller is adapted to store historical data of past driving and travel patterns for the electric vehicle and the operator of the electric vehicle.

DETAILED DESCRIPTION

Referring toFIG. 1, a system10for providing a pre-conditioning prompt to an operator of an electric vehicle12comprises a controller14in communication with the electric vehicle12and the operator16of the electric vehicle12. An operator interface18is adapted to allow the operator16of the electric vehicle12to communicate with the controller14.

The controller14is a non-generalized, electronic control device having a preprogrammed digital computer or processor, memory or non-transitory computer readable medium used to store data such as control logic, software applications, instructions, computer code, data, lookup tables, etc., and a transceiver or input/output ports. Computer readable medium includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A “non-transitory” computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device. Computer code includes any type of program code, including source code, object code, and executable code.

The operator interface18is integral to a personal device20belonging to and carried by the operator16of the electric vehicle12. The operator16of the electric vehicle12communicates with the controller14and is able to respond to prompts from the controller14through the operator interface18of the personal device20. The personal device20may be any device adapted to allow two-way communication between the operator16of the electric vehicle12and the electric vehicle12, such as an operator's cell phone, smart phone, tablet, laptop computer, or smart watch.

The controller14is adapted to track the position of the electric vehicle12, track the position of the operator16of the electric vehicle12, access historical data, access weather information, and send a prompt to the operator16of the electric vehicle12when the controller14identifies conditions indicating use of the electric vehicle12is imminent, or likely to happen soon, and the temperature where the electric vehicle12is located necessitates pre-conditioning of an electric propulsion system22within the electric vehicle12.

The system10utilizes GPS24and GPS capability within the personal device20to track the location of the operator16of the electric vehicle12, and communication between the electric vehicle12and the personal device20is over a cellular network26. The cellular network26is a radio network distributed over land through cells where each cell includes a fixed location transceiver known as a base station. These cells together provide radio coverage over larger geographical areas. Equipment, such as mobile phones, are therefore able to communicate even if the equipment is moving through cells during transmission.

Further, the controller14is adapted to access information from the internet to identify the nature of an activity at a destination, and calculate an average length of time for the identified activity to conclude based on data from the internet. Using the calculated average length of time for the identified activity to conclude, the controller14can predict how long the operator of the electric vehicle12will remain at the destination. The controller14also uses information from the internet to determine weather conditions.

In addition, the controller14is adapted to store historical data of past driving and travel patterns for the electric vehicle12and the operator16of the electric vehicle12. The controller14can use stored historical data to predict travel patterns and the length of time the operator16of the electric vehicle12will remain at a location based on past patterns.

Referring toFIG. 2, a method30of prompting an operator16of an electric vehicle12for pre-conditioning the electric vehicle12, comprises monitoring32a location of the electric vehicle12, monitoring34the temperature of the electric propulsion system22within the electric vehicle12, accessing36historical data of driving patterns for the electric vehicle12, monitoring38the location of the operator16of the electric vehicle12, and identifying40a condition that indicates imminent usage of the electric vehicle12based on the location of the vehicle12, the location of the operator16of the electric vehicle12, and the historical data of driving patterns for the electric vehicle.

Once a condition of imminent usage of the electric vehicle is identified40, the controller14compares42the temperature of the electric propulsion system22of the electric vehicle12to a pre-determined preferred operating temperature. Operation of the electric propulsion system below established preferred operating temperatures results in less efficiency, lower power output and shorter battery life. Therefore, it is important that the electric vehicle12, and particularly the batteries of the electric propulsion system22, be operated above the pre-determined preferred operating temperature.

If the temperature of the propulsion system22within the electric vehicle12is below the pre-determined preferred operating temperature, the controller14sends44a prompt to the operator16of the electric vehicle12suggesting that pre-conditioning of the electric vehicle12may be appropriate. The operator has the option, once prompted44, to respond to the controller14via the operator interface18, and initiate pre-conditioning of the electric propulsion system22.

The system10monitors32the location of the operator16of the electric vehicle12by accessing46the personal device20belonging to the operator16of the vehicle12, and using48GPS capability within the personal device20to monitor32the location of the operator16of the electric vehicle12.

Referring toFIG. 3, in an exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by monitoring50the arrival of the electric vehicle12at a public transportation hub. After the electric vehicle12arrives at a public transportation hub, such as, by way of non-limiting example, an airport, a bus depot, a train station, car rental agency, or a cruise ship dock, the controller monitors52movement of the operator16of the electric vehicle12from the public transportation hub to at least one location distant from the public transportation hub. The controller continues to monitor52movement of the operator16of the electric vehicle12, while the electric vehicle12remains located at the public transportation hub. The controller further monitors54the return of the operator16of the electric vehicle12to the public transportation hub.

Monitoring54the return of the operator16to the electric vehicle12after traveling to another destination via public transportation may be an indication that the operator16of the electric vehicle12is on route back to the electric vehicle12to leave the public transportation hub. If temperature conditions warrant, the controller will send44a prompt to the operator16of the electric vehicle12, giving the operator the opportunity to initiate pre-conditioning of the electric vehicle12.

Referring toFIG. 4, in another exemplary embodiment, the controller14accesses56the personal device20, identifies58travel plans from the personal calendar or uploaded itineraries of the operator16of the electric vehicle12, and predicts60the return of the operator16of the electric vehicle12to the public transportation hub based on data from the personal calendar and uploaded itineraries of the operator16.

Referring toFIG. 5, in another exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by monitoring62movement of the electric vehicle12to a destination, accessing64the personal device20of the operator16, identifying66travel plans from the operator's personal calendar or uploaded itineraries, and predicting68how long the operator16of the electric vehicle12will remain at the destination based on data from the operator's personal calendar and uploaded itineraries.

Referring toFIG. 6, in another exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by prompting70the operator16of the electric vehicle12for planned departure time, receiving72input from the operator16of the electric vehicle12of the planned departure time, and predicting74how long the operator16of the electric vehicle12will remain at the destination based on the planned departure time received from the operator16of the electric vehicle12. This allows the operator16of the electric vehicle12to input information to the controller14ahead of time, so the controller14has an accurate time when the operator should be prompted44to pre-condition the electric vehicle12.

Referring toFIG. 7, in another exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by monitoring76movement of the electric vehicle12to a destination, identifying78the destination, and predicting80how long the operator16of the electric vehicle12will remain at the destination.

By way of a non-limiting example, the electric vehicle12may arrive at a charging station. The controller14of the electric vehicle12monitors the systems within the electric vehicle12, so the controller14knows when the electric vehicle12is plugged in, if charging is taking place, and if charging stops. If an electric vehicle12is at a public charging station and detects that charging has stopped, the controller14can predict that the operator of the electric vehicle12will likely be returning to the electric vehicle12soon to move it from the public charging station.

Charging may stop due to the electric vehicle12being completely charged, or when the time allotted by the charging station has expired. In either instance, timed charging stations may be treated like a parking meter, where if an electric vehicle12is left at a public charging station after the allotted time has expired, or after charging of the electric vehicle12is complete, the electric vehicle12may be ticketed. Therefore, when the controller14detects that the electric vehicle12is fully charged, or that charging has stopped, the controller14can predict that the operator of the electric vehicle12will likely return soon to move the electric vehicle12from the charging station.

Referring toFIG. 8, in another exemplary embodiment, the controller predicts80how long the operator16of the electric vehicle12will remain at the destination by accessing82historical data, identifying84past instances where the electric vehicle12and the operator16traveled to the destination, calculating86an average time that the operator16spends at the destination, and predicting88how long the operator16of the electric vehicle12will remain at the destination based on the average time the operator16of the electric vehicle12spends at the destination.

By way of non-limiting example, the operator may travel to a hair salon. The controller14identifies78the destination is a hair salon. The controller14accesses82historical data to look for other instances where the operator16and the electric vehicle12traveled to the hair salon. The controller14calculates that the operator16spends, on average, forty-five minutes at the hair salon. Based on that average time, the controller14predicts88that the operator16will remain at the hair salon for approximately forty-five minutes, and sends44a prompt to the operator16after forty minutes, giving the operator16the opportunity to initiate pre-conditioning of the electric vehicle12.

By way of another non-limiting example, the operator may travel to a frequently travelled location to charge the electric vehicle12. The controller14may identify that the electric vehicle12is at a charging station based on GPS, or alternatively, the controller14may detect the electric vehicle12is at a charging station by detecting when the electric vehicle12is plugged in and charging commences. The controller14can predict, based on data from previous charging events, how long the electric vehicle12will likely be plugged in before the electric vehicle12will once again be used. The controller14may also detect when charging of the electric vehicle12is near completion by monitoring the level of charge in the electric vehicle12.

Referring toFIG. 9, in another exemplary embodiment, the controller predicts80how long the operator16of the electric vehicle12will remain at the destination by accessing90information from the internet, identifying92the nature of the activity at the destination, calculating94an average length of time for the identified activity to conclude based on data from the internet, and predicting96how long the operator16of the electric vehicle12will remain at the destination based on the average length of time for the identified activity to conclude.

By way of non-limiting example, the operator may travel to a hair salon. The controller14identifies78the destination is a hair salon. The controller14accesses90the internet to identify the type of activity that takes place at the hair salon and how long such activity generally takes. The controller determines from internet data that the most common activity at the hair salon is a hair cut, and on average, a hair cut takes approximately twenty-five minutes. Based on that average time, the controller14predicts96that the operator16will remain at the hair salon for approximately twenty-five minutes, and sends44a prompt to the operator16after twenty minutes, giving the operator16the opportunity to initiate pre-conditioning of the electric vehicle12.

Referring toFIG. 10, in another exemplary embodiment, the controller predicts80how long the operator16of the electric vehicle12will remain at the destination by accessing98the operator's personal device20, monitoring100financial transactions and electronic payments made by the operator16using the personal device20, identifying102a payment made at the destination, and predicting104how long the operator16of the electric vehicle12will remain at the destination based on identifying102a payment made by the operator16at the destination.

By way of non-limiting example, the operator may travel to a hair salon. The controller14identifies78the destination is a hair salon. The controller14accesses98the personal device20of the operator16and monitors100electronic payments made by the operator16. The controller identifies102that an electronic payment has been made by the operator16at the destination. Based on a payment being made by the operator16, the controller14predicts104that the operator16may soon depart and sends44a prompt to the operator16, giving the operator16the opportunity to initiate pre-conditioning of the electric vehicle12.

In another exemplary embodiment, the controller predicts how long the operator of the electric vehicle will remain at the destination by detecting when the electric vehicle is parked at a public parking facility, accessing a parking application on the operator's personal device, monitoring when a pre-paid parking time will expire, and predicting how long the operator of the electric vehicle will remain at the charging station based on pending expiration of the pre-paid parking time.

By way of non-limiting example, the operator may travel to a hair salon. The controller14identifies that the electric vehicle has been parked at the public parking lot across the street from the hair salon. The controller14accesses a parking application on the personal device20of the operator16and monitors electronic payments made by the operator16. The controller identifies that an electronic payment has been made by the operator16to pay for thirty minutes of parking at the public parking lot. Based on a payment being made by the operator16for a pre-determined amount of time, thirty minutes, the controller14predicts that the operator16may depart after thirty minutes and sends44a prompt to the operator16, giving the operator16the opportunity to initiate pre-conditioning of the electric vehicle12ahead of time.

Referring toFIG. 11, in another exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by accessing106the operator's personal device20, identifying108recurring planned departures from the personal calendar on the personal device20, and predicting110future departures based on data from the operator's personal calendar.

Referring toFIG. 12, in another exemplary embodiment, the controller14identifies40a condition that indicates imminent usage of the electric vehicle12by identifying112patterns of past recurring departures from the historical data and predicting114future departures based on patterns of recurring past departures.

By way of non-limiting example, the operator16of the electric vehicle goes to the hair salon on the first Tuesday of every month at 2:00 p.m. The controller identifies112this recurring pattern, and based on the recurring pattern, sends44a prompt to the operator16of the electric vehicle at 1:50 p.m. on the first Tuesday of the following month.