PREDICTING  CONSUMPTION AND RANGE OF A VEHICLE BASED ON COLLECTED ROUTE ENERGY CONSUMPTION DATA

A method for a vehicle, a vehicle and a server are described.

DETAILED DESCRIPTION OF THE INVENTION

In the following, exemplary embodiments of the invention will be described in more detail. It is to be understood that the following description is given only for the purpose of illustrating the principles of the invention and is not to be taken in a limiting sense. Rather, the scope of the invention is defined only by the appended claims and is not intended to be limited by the exemplary embodiments hereinafter.

It is to be understood that in the following detailed description of the various embodiments, any direct connection or coupling between functional blocks, devices, components or other physical or functional units shown in the drawings or described herein could also be implemented in an indirect connection or coupling. Same reference signs in the various instances of the drawings refer to similar or identical components. It is furthermore to be understood that the features of the various exemplary embodiments described herein may be combined unless specifically noted otherwise.

Currently, electrical vehicles comprising for example an electrical engine and a battery, provide shorter driving ranges than vehicles comprising a combustion engine. Furthermore, charging the battery of the electrical vehicle may require more time than refueling a combustion engine vehicle. Therefore, an output to a driver of an electrical vehicle indicating a remaining driving range of the vehicle is crucial. However, the remaining driving range of an electrical vehicle may be influenced significantly by for example the elevation profile, the speed travelled, and other parameters which are not transparent to the driver. Therefore, the driver may not trust the remaining driving range indications.FIG. 1shows an exemplary output of a remaining driving range of an electrical vehicle. Graphs1,2and3indicate the remaining driving range output to the driver over time. The graphs4and5indicate the distance driven by the vehicle over time. Starting at time t0, the driver is driving a route or road section going up- and downhill. Therefore, although the amount of driven kilometers indicated by graph4increases essentially continuously, the output of the remaining driving range as indicated by graph1varies significantly. This may confuse the driver. At time t1, the vehicle is recharged and the remaining driving range increases continuously as indicated by graph2. The driver continues driving at time t2. Again, as indicated by graph3, the remaining driving range varies significantly and increases and decreases although the distance driven since the last charging of the vehicle increases continuously as indicated by graph5.

The remaining driving range indication described above in connection withFIG. 1may be estimated as in combustion engine vehicles. First, it is determined how much fuel or energy is used right now and based on this and the remaining fuel in the tank or energy in the battery it is determined how far the vehicle is able to go assuming that the energy consumption continues like this. Especially in hilly areas or along road sections where continuous driving is not possible, the estimation of the remaining driving range varies as indicated inFIG. 1, which makes the driver of the vehicle not to trust the indicated remaining driving range.

Therefore, according to a method for a vehicle according to an embodiment of the present invention, at least one energy consumption of at least one other vehicle driving along a road section is measured and based on the at least one measured energy consumption of the at least one other vehicle an energy consumption of the vehicle required for driving along the road section is predicted. Furthermore, a current state of operation of the vehicle may be determined. The current state of operation may comprise for example a required cabin temperature, the weight of the vehicle, and a driving style of the driver like sportive or energy-conserving. Predicting the energy consumption of the vehicle may be performed furthermore based on this current state of operation. Furthermore, a road section information associated with structural properties of the road section may be determined. The road section information may comprise for example if the road section is part of a city or a highway, or if it is a winding or hilly road. Furthermore, the road section information may comprise a kind of road surface, for example if it is a paved road or a gravel road. Additionally, environmental conditions along the road section may be determined. The environmental condition may be associated with current weather conditions or traffic conditions along the road section. For example, the weather conditions may comprise a temperature, a wind speed or wind direction, and a precipitation. The traffic conditions may indicate a current average speed along the road section or if there is a traffic jam. The energy consumption of the vehicle required for driving along the road section may be determined based on the determined environmental conditions.

According to an embodiment, the at least one energy consumption of the at least one other vehicle is retrieved from a server. While the vehicle is driving along the road section, the energy consumed by the vehicle is measured and the measured energy consumption of the vehicle is provided to the server. Thus, the vehicle can provide energy consumption information to the server which may be provided by the server to other vehicles driving along the same road section.

In other words, all electric vehicles or at least a large number of electric vehicles report to the server how much energy they use for each road section or stretch they were driving along. This information is compiled in a central location and aggregated together with relevant information concerning this specific vehicle, for example type, weight, current temperature and required temperature, and the driver, for example a more energy-conserving driver or a more sporty driver. Based on this information an accurate prediction can be made for a vehicle driving along the road section. Furthermore, the server may provide self-learning predictions taking into account for example historical data, for example historical weather information or time of the day based traffic information.

According to another embodiment, a method for a vehicle comprises determining road sections of a planned route along which a driver of the vehicle is planning to drive. Furthermore, for each road section at least one energy consumption of at least one other vehicle driving along the road section is measured, and the energy consumption of the vehicle required for driving along the road section is predicted based on the at least one energy consumption of the other vehicles. Furthermore, a current energy available in the vehicle is determined and a remaining driving range is calculated based on the current available energy and the predicted energy consumptions for the route sections of the planned route.

If the driver of the vehicle has the route guidance active or if the vehicle uses a predictive navigation, the vehicle may report the route or destination to the server together with a current state of charge of the battery of the vehicle. The server may calculate the remaining driving range based on these parameters and the energy which has been used on the sub-sections of the route by other electrical vehicles in the past. The energy which has been used by the other vehicles in the past considers for example how much recuperation is possible on the route section and how much real braking is needed when going downhill. Furthermore, the driving range is based on the weather and temperature profile along the route and on how the driver usually uses the heating system and air conditioning system of the vehicle to compensate. Furthermore, the driving range may be predicted based on traffic information indicating if there is a traffic jam or if the user can go full speed. Furthermore, driver characteristics may be used to predict the remaining driving range, for example the top speed the driver usually goes or the driving style of the driver, for example if the driver accelerates rapidly or more moderately. The resulting remaining predicted driving range is sent back from the server to the vehicle and displayed to the driver.

The server may comprise a single server or a group of servers arranged in a network, in a so-called cloud. From the point of view of the vehicle, the architecture of the cloud is not relevant. However, a cloud-based architecture may provide a higher reliability for predicting the energy consumption or for calculating the remaining driving range.

According to another embodiment, a vehicle comprising a processing unit and a transmission unit is provided. The transmission unit allows the processing unit to communicate with a server outside the vehicle, for example a server in a so-called cloud network. In operation, the processing unit may retrieve a predicted energy consumption required for driving along a road section from the server. The predicted energy consumption is predicted by the server based on at least one energy consumption which has been measured by at least one other vehicle driving along the road section.

According to an embodiment, the processing unit determines furthermore a current state of operation of the vehicle and transmits the current state of operation to the server for predicting the energy consumption of the vehicle along the road section based on the determined current state of operation. Additionally, or as an alternative, the processing unit itself may predict the energy consumption of the vehicle for driving along the road section based on the determined current state of operation.

According to a further embodiment, the processing unit measures the energy consumption of the vehicle while the vehicle is driving along the road section. The measured energy consumption of the vehicle is then provided by the processing unit to the server.

Furthermore, the processing unit may determine road sections of a planned route along which a driver of the vehicle is planning to drive. For each road section the processing unit may retrieve from the server a predicted energy consumption required for driving along the corresponding road section. Furthermore, the processing unit may determine a current energy available in the vehicle and may calculate a remaining driving range of the vehicle based on the current available energy and the predicted energy consumptions for the route sections of the planned route.

According to yet another embodiment, a server comprises a transmission unit to communicate with at least one first vehicle and a second vehicle, and a processing unit. The processing unit may receive from the at least one first vehicle at least one measured energy consumption indicating an energy consumed by the first vehicle driving along a road section. Furthermore, the processing unit may predict an energy consumption of the second vehicle required for driving along the road section based on the at least one measured energy consumption from the first vehicles. The processing unit may provide the predicted energy consumption to the second vehicle.

According to an embodiment, the processing unit of the server may furthermore receive a current state of operation of the second vehicle from the second vehicle and may predict the energy consumption of the second vehicle required for driving along the road section additionally based on the received current state of operation.

According to another embodiment, the processing unit of the server may determine a road section information associated with structural properties of the road section, for example if the road section is a road in a city or a road of a highway, or if the road section is a winding road through mountains or along a coast, and so on. Based on the determined road section information, the processing unit may predict the energy consumption of the second vehicle required for driving along the road section.

Additionally, the processing unit of the server may determine environmental conditions along the road section which are associated with for example weather conditions or traffic conditions along the road section. Based on the determined environmental conditions the processing unit may predict the energy consumption of the second vehicle required for driving along the road section. The predicted energy consumption may be transmitted by the processing unit via the transmission unit to the second vehicle.

FIG. 2shows a communication structure between a vehicle10and a server11according to an embodiment. The server11comprises a transmission unit12and a processing unit13. As shown inFIG. 3in more detail, the vehicle10comprises a transmission unit18and a processing unit19. The vehicle10is an electrical vehicle comprising an electrical engine20for propelling the vehicle10and a battery21for supplying electrical energy to the electrical engine20. The vehicle10comprises furthermore a display22indicating a remaining driving range for the vehicle to the user of the vehicle.

The server11is coupled to a data base14for storing information about the vehicle10and the driver. In the data base14, for example a driver characteristic of the driver driving the vehicle10may be stored. The driver characteristics may comprise for example if a driving style of the driver is more sporty or more energy-conserving. Furthermore, the driver characteristics may comprise information about a top speed the driver usually goes or a preferred cabin temperature of the driver. The information about the vehicle may comprise for example a weight of the vehicle and information about an aerodynamic resistance of the vehicle. The server11is furthermore coupled to a server15providing road network data. The road network data may comprise for example information about an elevation or slope of a road, or a kind of road, for example if the road is in an urban environment inside a city, or if it is part of a highway. The server11is furthermore coupled to a traffic information server16and a weather information server17. The traffic information server16may provide information about congestions or traffic jams and a current average speed on specific road sections. The weather information server17may provide weather information like temperature, precipitation, wind speed and sun intensity along road sections. The server11, the data base14and the server15for the road network data may be operated by a vehicle provider whereas the traffic information server16and the weather information server17may be operated by a separate content provider. However, this is just an exemplary segmentation and any other kind of segmentation may be implemented. Especially, the servers11and15-17may constitute a so-called data information cloud.

Operation of the vehicle10and the server11will now be described in connection with the method40shown inFIG. 4in more detail. If a driver of the vehicle10has activated the route guidance for guiding the vehicle to a destination or if the vehicle uses a predictive navigation, the processing unit19of the vehicle10determines in step41road sections of the route to the destination. The processing unit19transmits the determined road sections via the transmission unit18to the server11. The processing unit13of the server11receives the road sections via the transmission unit12. As an alternative, the processing unit19of the vehicle may transmit the destination to the server11and the processing unit13of the server11may determine the road sections to the destination.

The processing unit13of the server11retrieves in step42for each road section an amount of energy which has been consumed by other vehicles which have driven along this road section in the past. In step43, the processing unit13predicts a required energy for the vehicle10to drive along each of the road sections. For predicting the required energy, the processing unit13may consider additional information from the data base14, the traffic information server16, the weather information server17and the road network data server15. Thus, the processing unit13of the server11can make a very precise energy consumption prediction taking into account for example a weight of the vehicle10, current wind conditions, and the speed the vehicle10will drive along the road section due to the current traffic situation along the road section. Furthermore, the processing unit19of the vehicle10may transmit to the processing unit13of the server11a current state of operation of the vehicle. The state of operation of the vehicle may comprise for example a required cabin temperature the driver has set and a current outside temperature. Based on this additional information the processing unit13predicts the required energy for cooling or heating the cabin of the vehicle10and can thus predict the required energy for driving along the road section. The required energy for driving along the road section is transmitted from the server11to the vehicle10and the processing unit19of the vehicle10determines in step44a current energy level of the battery21. Based on the required energy for driving along the road sections of the planned route and the current energy level of the battery21, the processing unit19calculates in step45a remaining driving range of the vehicle10.

While exemplary embodiments have been described above, various modifications may be implemented in other embodiments. For example, additional states of operation of the vehicle may be considered for predicting the required energy in step43. For example, an activation state of windshield wipers, headlamps or a music entertainment system of the vehicle may be considered for predicting the required energy. Finally, it is to be understood that all the embodiments described above are considered to be comprised by the present invention as it is defined by the appended claims.