Navigation method for an electric motor vehicle

Abstract

A navigation method for an electric motor vehicle comprises the steps of: acquiring (201) a destination point; determining (203) a route to reach the destination point, the determination including a substep of determining the necessary electric charging stops (211, 213, 215) based on the anticipated electrical consumption, the vehicle's battery capacity and state of charge, and the geographical location of charging stations; and the determination of the electric charging stops further taking into account the number of terminals at each charging station. A navigation device and a motor vehicle comprising the device are also described. Figure to be published with the abbreviation: Fig 2

Description

Title of the invention: Navigation method for an electrically powered motor vehicle. Technical field

[0001] The present invention relates to a navigation method for an electric motor vehicle, a navigation device for an electric motor vehicle, a motor vehicle comprising such a device and a computer program product. State of the art

[0002] One of the problems with electric vehicles is that of recharging them. As soon as a journey exceeds the battery range, it is necessary to plan a stop along the way to recharge the batteries at a station.

[0003] To assist drivers, most navigation systems for this type of vehicle incorporate route calculations by passing through charging stations, and the stages between stations are calculated based on the vehicle's energy range, i.e., taking into account both the battery's charging capacity and its state of charge at the time of calculation.

[0004] For the most sophisticated navigation systems, travel time will be minimized by taking into account, on the one hand, the capacity of high-density or fast-charging stations, and, on the other hand, the availability of charging points. To achieve this, using 4G / 5G wireless networks, the navigation system queries databases that contain, in near real-time, the occupancy rate of charging points. This makes it possible to minimize waiting times before charging.

[0005] However, this has the drawback of only working when the navigation system has access to a network connection. If the vehicle is in an area not covered by a network, this optimization does not work, and the navigation system then calculates the route in a degraded mode, often taking into account only the types of charging stations and their relative distances.

[0006] There is therefore a real need for a navigation method and system for an electric motor vehicle which resolves all or part of the aforementioned disadvantages. Description of the invention

[0007] To overcome one or more of the aforementioned drawbacks, according to a first embodiment, a navigation method for an electrically powered motor vehicle is implemented by a processor and comprises the steps of: • collection of a destination point; • Determining a route to reach the destination, including a sub-step of determining the necessary electric charging stops based on anticipated electricity consumption, the vehicle's battery capacity and state of charge, and the geographical location of charging stations; and • The determination of electric charging stages also takes into account the number of terminals at each charging station.

[0008] Thus, navigation can advantageously use a proxy of the percentage of use of the terminals to find a station whose probability of waiting time is minimized.

[0009] Specific features or embodiments, usable alone or in combination, are: • the determination of the route includes a calculation to minimize the foreseeable travel time and said calculation gives a time weight dependent on the number of terminals at each charging station; • the time weight includes a predicted waiting time before recharging for each station; • The estimated waiting time decreases with the number of terminals in the station; • the minimization calculation selects a charging station with the lowest predicted waiting time, provided that the driving time to reach this station is not greater than a predetermined time interval relative to another station; • The predetermined time interval includes the difference between the waiting times between the two stations; and / or • the predetermined time interval is less than the difference between the waiting times minus a constant.

[0010] In a second embodiment, a device includes a memory associated with at least one processor configured to implement the method of the first embodiment.

[0011] In a third embodiment, a motor vehicle includes a device according to the second embodiment

[0012] In a fourth embodiment, a computer program includes instructions which, when the program is executed by the device according to the second embodiment, lead the device to implement the process according to the first embodiment. Brief description of the figures

[0013] The invention will be better understood upon reading the following description, given solely by way of example, and with reference to the figures in the appendix in which: • [Fig. 1] represents a top view of a navigation device according to one embodiment; and • [Fig.2] represents a flowchart of a navigation process according to one embodiment. Methods of implementation

[0014] The embodiments presented below refer to a motor vehicle, a car, and more specifically an electric car. However, those skilled in the art understand that these embodiments are also applicable to other types of vehicles, such as vans, trucks, etc. Other applications, such as a motorcycle on a country road, are also conceivable.

[0015] The terms "front", "rear", "top", "bottom", "transverse" are understood in relation to the vehicle.

[0016] Figure 1 shows an example of a device 101 included in the vehicle. This device 101 can be used as a centralized device responsible for at least some steps of the process described below with reference to Figure 2. In one embodiment, it corresponds to a navigation computer.

[0017] This device 101 can take the form of a housing comprising printed circuits, any type of computer or even a mobile phone ("smartphone"). This device is sometimes called a computer or ECU (from the English acronym "Electronic Control Unit").

[0018] The device 101 includes a random access memory 103 for storing instructions for implementation by a processor 105 of at least one step of the method as described below. The device also includes a mass storage 107 for storing data intended to be retained. In particular, the mass storage 107 stores the mapping necessary for vehicle navigation and a database of points of interest. Among these points of interest, the database contains the locations of charging stations with the number and characteristics of the charging points at each station.

[0019] The device 101 also includes a person-machine interface 109 in the form of a touch screen allowing both the display of a map and the entry of a destination or the selection of a destination point of interest.

[0020] The device 101 also includes a transmitter 111 for communication with a 4G / 5G or WiFi network. This transmitter allows, in particular, the updating of the data contained in the mass memory 107.

[0021] Device 101 can, for example, be integrated into the vehicle's control system as an advanced driver-assistance system, commonly known as ADAS (for "Advanced Driver-Assistance Systems"), which makes all driving decisions based on the environment and the programmed destination. The motor vehicle is then described as an autonomous vehicle. However, it can also be a centralized vehicle management system that may or may not include driver assistance features.

[0022] Data transfer between the different elements is preferably carried out by a CAN (for "Controller Area Network") or LIN (for "Local Interconnect Network") type data bus.

[0023] The operation of device 101 is as follows, [Fig.2].

[0024] The user enters a destination or destination point of interest via the touch screen 109, step 201.

[0025] Processor 105 then launches a route calculation algorithm, step 203.

[0026] It begins by checking if a network is available, step 205. If a network is available, it continues the route calculation using known methods, such as those explained in the preamble, step 207.

[0027] If no network is accessible, the processor 105 starts the route calculation using only the data contained in mass memory 107, step 209.

[0028] The route determination is then carried out as follows, given that the algorithm for finding an efficient route, in the sense of a route that minimizes the time to reach the destination, has a "classic" mode of operation well known to those skilled in the art. It begins by determining whether the route will require one or more charging stops based on the anticipated electricity consumption, the capacities and state of charge of the vehicle's batteries, and if so, it will estimate the number of charging stops required, step 211. For each charging stop, it will determine a list of charging stations that could potentially be used, step 213.

[0029] The distinctive feature of the method described here is that, in step 215, when selecting a station from the list of stations, it considers the number of charging points at each station, assuming that the more points a station has, the lower the risk of waiting. To achieve this, it incorporates into the travel time minimization calculation a time spent charging at a station, including the actual charging time, which is generally fixed, and a foreseeable waiting time associated with the possibility that all of a station's points might be occupied.

[0030] The calculation then assigns a temporal weight to the number of terminals at the station, preferably in the form of a decrease in the expected waiting time as the number of terminals increases. This can be, for example, a 1 / x relationship.

[0031] Thus, in the absence of real-time information on the occupancy of the terminals of a station, an approximation associated with the number of terminals still makes it possible to choose a station from which one can expect a limited waiting time.

[0032] Figure 1 illustrates a system according to certain embodiments. The breakdown presented is for pedagogical purposes to highlight the different functions. However, it is understood that each block can be implemented using different means or combinations thereof, such as hardware components, software, one or more computers, and / or electronic circuits. Each component may include at least one computer or a control unit. At least one memory may be included in each component. The memory may include computer program instructions or software code.

[0033] The computers can be implemented by any type of data processing device, such as a central processing unit, a signal processing unit, a specific application integrated circuit, a programmable gate network, etc. The computers can be implemented in the form of a single controller, or a plurality of controllers or computers.

[0034] The different modules are connected to each other by data links adapted to the environment. These can be wired, electrical or optical, or wireless.

[0035] For the software, the implementation may comprise modules or units distributed in the form of procedures, functions, etc. The memories may be any type of storage circuit. They may be part of the processor circuit, or separate from it and connected via electrical data links. These may be non-volatile memories, hard drives, RAM, flash memory, etc.

[0036] The software product can be downloaded from a communication network and / or stored on a computer-readable medium. It can be directly executable by a processor or be in the form of a high-level language requiring one or more intermediate operations to be executable.

[0037] Thus, the program instructions stored in memory and processed by the computers can be any type of program code, for example, a compiled or interpreted program written in a suitable programming language.

[0038] The computer program instructions stored in memory are such that, when executed by the computer, the latter carries out one or more of the steps of the processes described above.

[0039] The invention has been illustrated and described in detail in the preceding drawings and description. The latter should be considered illustrative and given by way of example and not as limiting the invention to this single description. Numerous embodiments are possible.

[0040] For example, the process has been described as a sequence of steps. Some steps can be carried out in parallel or in a different sequence.

[0041] Equations and calculations have also been detailed. The invention is not limited to the form of these equations and calculations, and extends to any other type of mathematically equivalent form.

[0042] In a first embodiment, the travel time to reach the station is also taken into account in the station selection step. Indeed, not all stations are at the same distance, and some may involve a substantial increase in the distance to be covered. It could then be counterproductive to go to a station with a short expected waiting time, but with a substantially increased travel time that would, in a way, replace the waiting time. To address this, it is possible, for example, to include in the calculation for each station the delta of the increase in travel time compared to the most direct station and to add this delta to the expected waiting time. An equivalent method is to determine a delta of travel time that does not exceed a predetermined time interval, either compared to the most direct station or by comparing two stations in the list.This predetermined time can correspond to the difference between the waiting times between the two stations to which we can, or not, add a constant to take into account the fact that the duration of a journey is quite predictable while the waiting time, due to the lack of knowledge of the actual state of occupancy of the terminals, has a greater uncertainty.

Claims

Demands

1. Navigation method for an electric motor vehicle, said method being implemented by a processor and comprising the steps of: • collecting (201) a destination point; • determining (203) a route to reach the destination point, the determination comprising a substep of determining the electric charging stages (211, 213, 215) necessary based on the foreseeable electric consumption, the capacities and state of charge of the vehicle's batteries on the one hand and the geographical locations of the charging stations on the other hand; and • the determination of the electric charging stages further taking into account the number of terminals at each charging station.

2. A method according to claim 1, wherein the determination of the route includes a calculation to minimize the foreseeable time of the route, and said calculation gives a time weight dependent on the number of terminals at each charging station.

3. Method according to claim 2, wherein the time weight includes a predicted waiting time before recharging for each station.

4. A method according to claim 3, wherein the predicted waiting time decreases with the number of terminals in the station.

5. A method according to claim 4, wherein the minimization calculation selects a charging station with the lowest predicted waiting time provided that the driving time to reach this station is not greater than a predetermined time interval relative to another station.

6. A method according to claim 5, wherein the predetermined time interval comprises the difference between the waiting times between the two stations.

7. A method according to claim 6, wherein the predetermined time interval is less than the difference between the waiting times less a constant.

8. Device (101) comprising a memory (103) associated with at least one processor configured to implement the method according to one of the preceding claims.

9. Motor vehicle comprising the device according to the preceding claim.

10. Computer program product comprising program code instructions which, when the program is executed by the device according to claim 8, cause the device to implement the method according to any one of claims 1 to 7.

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