Apparatus and method for estimating energy use of an electric drivetrain

Abstract

A control system, comprising a memory 226 and one or more processors (224-Fig.2B), estimates future energy usage of an electric drivetrain (220-Fig.2A) of a vehicle. The control system: stores a pred

Description

TECHNICAL FIELD The present disclosure relates to an apparatus and methods for estimating the future energy usage of an electric drivetrain of a vehicle. Aspects of the invention relate to a control system for estimating energy usage of an electric drivetrain of a vehicle, a system including the control system, a vehicle, and to a method for estimating energy usage of an electric drivetrain of a vehicle. BACKGROUND For vehicles with electric drivetrains it is known to estimate the energy usage of a future journey based on a predetermined average energy usage per unit distance. Such information may be useful for estimating a range of the vehicle, for planning recharging, or for informing the driver of the predicted remaining battery energy at arrival. However, there are numerous variables and different vehicle configurations that affect the energy usage per unit distance and would thereby cause inaccuracies when relying on predetermined energy usage data. It is an aim of the present invention to address one or more of the disadvantages associated with the prior art. SUMMARY OF THE INVENTION Aspects and embodiments of the invention provide a control system for estimating energy usage of an electric drivetrain of a vehicle, a system including the control system, a vehicle, and to a method for estimating energy usage of an electric drivetrain of a vehicle as claimed in the appended claims. According to an aspect of the present invention there is provided a control system for estimating future energy usage of an electric drivetrain of a vehicle, the control system comprising a memory and one or more processors collectively configured to: store a predetermined average electrical power usage for each of a plurality of discrete speed ranges, receive a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle, receive a signal indicative of a corresponding vehicle speed of the vehicle, and update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges. Advantageously, the moving average electrical power usages are thereby based on the actual use of the vehicle, and thus are adapted to the configuration of the vehicle. This may provide more accurate power usage data for estimating the future energy use of the vehicle, for example for a planned or expected journey. In examples, the memory and the one or more processors may be collectively configured to: in dependence on the moving average electrical power usages, determine an expected energy usage for a future journey and output a signal indicative thereof, and in dependence on the signal indicative of the expected energy usage, display one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. Advantageously, the moving average electrical power usages are thereby used to determine a more accurate expected energy usage for the future journey because the moving average data is based on the vehicle and so takes account of vehicle configuration. Beneficially, the user (e.g., a driver) is provided with the expected vehicle range, state of charge, and / or energy usage, which has improved accuracy to the specific vehicle. The control system comprises one or more controllers collectively comprising at least one electronic processor having an electrical input for receiving an input signal; and at least one memory device electrically coupled to the at least one electronic processor and having instructions stored therein; and wherein the at least one electronic processor is configured to access the at least one memory device and execute the instructions thereon so as to: store a predetermined average electrical power usage for each of a plurality of discrete speed ranges, receive a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle, receive a signal indicative of a corresponding vehicle speed of the vehicle, update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges, in dependence on the moving average electrical power usages, determine an expected energy usage for a future journey and output a signal indicative thereof, and in dependence on the signal indicative of the expected energy usage, display one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. Advantageously, the moving average electrical power usages are thereby based on the actual use of the vehicle, and thus are adapted to the configuration of the vehicle. This may provide more accurate power usage data for estimating the future energy use of the vehicle, for example for a planned or expected journey. In examples, the state of charge at a future time or location may comprise one or more of: a state of charge at the end of the future journey, or a state of charge at a time or location during the future journey. Advantageously, the user is thereby provided with a more accurate estimation of the state of charge of the battery, which may improve route planning by, for example, providing information that may be used to plan charging. In examples, the predetermined and moving average electrical power usages are stored as the energy per unit distance (e.g. in Wh / km), i.e., the average energy required for the drivetrain to move the vehicle a predetermined distance, such as 1 km. In examples, the signal indicative of the electrical power usage of the electric drivetrain is an instantaneous power measurement, for example measured in kW. In such examples, the memory and the one or more processors may be collectively configured to convert the received instantaneous power measurement into an energy per unit distance based on the received signals indicative of the electrical power usage and the corresponding vehicle speed. Advantageously, this may reduce the amount of data to be stored in the memory and reduce processing power required to determine the moving average electrical power usages. In various examples, the moving average may be a simple moving average, a cumulative moving average, a weighted moving average, or an exponentially weighted moving average. Advantageously, different types of moving averages may provide faster or slower transition from the predetermined average electrical power usages, which may reduce the volatility of the moving average values and improve the accuracy of the moving averages. I n examples, the future journey may comprise a plurality of journey sections and each journey section may have a predicted vehicle speed. The memory and the one or more processors may be collectively configured to determine the expected energy usage of the electric drivetrain for each journey section based on the moving average electrical power usage for the discrete speed range corresponding to each predicted vehicle speed of each journey section. Advantageously, the energy usage of the future journey may be more accurately predicted by dividing the journey into journey sections. In examples, for each discrete speed range, the memory and the one or more processors may be collectively configured to update the predetermined average electrical power usage to the moving average electrical power usage once the moving average electrical power usage is based on a threshold number of data points. Advantageously, this may help to improve accuracy by only changing to the moving average values once they are based on a threshold number of data points and are therefore considered representative of average driving conditions. This may reduce volatility in the determined expected energy usage for a future journey. In examples, for each discrete speed range, the memory and the one or more processors may be collectively configured to output a signal indicative of the expected energy usage for the future journey based on the predetermined average power usage until the moving average electrical power usage is based on a threshold number of data points. Advantageously, this may help to improve accuracy by only outputting the signal indicative of the expected energy usage for the future journey once the moving averages are based on a threshold number of data points and are therefore considered representative of average driving conditions. This may reduce volatility in the determined expected energy usage for a future journey. In examples, after updating the stored predetermined average electrical power usage to the moving average electrical power usage for a first discrete speed range of the plurality of discrete speed ranges, the memory and the one or more processors may be collectively configured to: determine a difference between the predetermined average electrical power usage and the moving average electrical power usage for the first discrete speed range, and based on the determined difference, apply a correction to the predetermined average electrical power usage of a second discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached. Advantageously, this may allow the predetermined average electrical power usages to be updated to moving averages more quickly, improving the accuracy of the determined expected energy usage for a future journey. In particular, some of the discrete speed ranges may take longer to reach the threshold number of data points because the vehicle may be driven less frequently at some speeds (e.g., higher speeds). Using the determined difference for the first discrete speed range to apply a correction to a second discrete speed range will improve the accuracy of the energy usage data for the second discrete speed range until enough data has been acquired for the second discrete speed range. In examples, after updating the stored predetermined average electrical power usage to the moving average electrical power usage for a first discrete speed range and a second discrete speed range of the plurality of discrete speed ranges, the memory and the one or more processors may be collectively configured to: determine an average difference between the predetermined average electrical power usages and the moving average electrical power usages for the first discrete speed range and the second discrete speed ranges, and based on the determined difference, apply a correction to the predetermined average electrical power usage of at least one further discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached. Advantageously, this may allow the predetermined average electrical power usages to be updated to moving averages more quickly, improving the accuracy of the determined expected energy usage for a future journey. In particular, some of the discrete speed ranges may take longer to reach the threshold number of data points because the vehicle may be driven less frequently at some speeds (e.g., higher speeds). Using the determined differences for the first and second discrete speed range to apply a correction to a further discrete speed range will improve the accuracy of the energy usage data for the further discrete speed range until enough data has been acquired for the further discrete speed range. In examples, the memory and one or more processors may be collectively configured to: determine a plurality of first moving average electrical power usages from a plurality of first data sets, each first data set having a first predetermined number of data points of the signals indicative of the received electrical power usage and the corresponding vehicle speed, and determine a second moving average electrical power usage from the plurality of first moving average electrical power usages. Advantageously, this may reduce the amount of data that needs to be stored to determine the moving average, and may also reduce the volatility of the moving average that is used to determine the expected energy usage of the future journey. In addition, the first and second moving averages can be stored in RAM on the vehicle and so can be stored during interruptions from driving (and data collection). Accordingly, it is possible to capture and use data from short drives that would usually not generate enough data to result in an updated first and / or second moving average. In examples, the memory and the one or more processors may be collectively configured to, in dependence on the second moving average electrical power usage, determine the expected energy usage for a future journey and output the signal indicative thereof. Advantageously, using the second moving average to determine the expected energy usage will reduce the volatility of the expected energy usage. In examples, the plurality of first data sets may correspond to the most recently received signals indicative of the received electrical power usage and the corresponding vehicle speed. In examples, the plurality of first data sets may comprise a fixed number of data sets, which is a subset of the total number of first data sets after the fixed number of data sets have been received. Advantageously, this may reduce the amount of data that is stored and allow the moving averages to adapt to changes in vehicle configuration (e.g., a change of wheels). In examples, the memory and one or more processors may be collectively configured to: determine a plurality of second moving average electrical power usages from a plurality of the first moving average electrical power usages, and determine a third moving average electrical power usage from the plurality of second first moving average electrical power usages. Advantageously, this may reduce the amount of data that needs to be stored to determine the moving average, and may also reduce the volatility of the moving average that is used to determine the expected energy usage of the future journey. In addition, the first, second and third moving averages can be stored in RAM on the vehicle and so can be stored during interruptions from driving (and data collection). Accordingly, it is possible to capture and use data from short drives that would usually not generate enough data to result in an updated first and / or second and / or third moving average. In examples, the memory and the one or more processors may be collectively configured to, in dependence on the third moving average electrical power usage, determine the expected energy usage for a future journey and output the signal indicative thereof. Advantageously, using the third moving average to determine the expected energy usage will reduce the volatility of the expected energy usage. In examples, during driving of the vehicle, the memory and the one or more processors may be collectively configured to receive a signal indicative of a road gradient. The signal may be determined from the received signals indicative of the electrical power usage and the vehicle speed. Advantageously, the road gradient may change the energy usage of the vehicle and so this information can be used to improve the determination of the moving averages and the expected energy usage. In examples, the memory and the one or more processors may be collectively configured to update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a predetermined range of the road gradient. In other words, the moving average is only determined using data obtained within the predetermined range of the road gradient. In examples, the predetermined range of the road gradient is a flat or substantially flat road gradient, for example a road gradient having an angle of less than ± 5 degrees from the horizontal, or less than ± 4 degrees from the horizontal, or less than ± 3 degrees from the horizontal, or less than ± 2 degrees from the horizontal, or less than ± 1 degree from the horizontal, or about horizontal. Advantageously, this may exclude data captured at steep gradients when determining the moving averages, which will make the moving averages more accurate to flat road driving conditions. In examples, the memory and the one or more processors may be collectively configured to: store a predetermined average electrical power usage for each of the plurality of discrete speed ranges and for each of a plurality of discrete road gradient ranges, update the stored predetermined average electrical power usages for each of the plurality of discrete speed ranges and each of the discrete road gradient ranges based on the received signals indicative of the electrical power usage, vehicle speed and road gradient to provide a moving average electrical power usage for each of the plurality of discrete speed ranges and for each of the plurality of discrete road gradient ranges. Advantageously, the stored moving averages and the determined expected energy usage are based on both the road gradient and speed and so the accuracy is improved. In examples, the memory and the one or more processors may be collectively configured to: store predetermined average electrical power usages for the plurality of discrete speed ranges for a solo vehicle, store predetermined average electrical power usages for the plurality of discrete speed ranges for a vehicle with a vehicle accessory, for example a trailer, receive a signal indicative of the presence or absence of the vehicle accessory, and update the stored predetermined average electrical power usages for the solo vehicle and the vehicle with the accessory based on the received signals indicative of the electrical power usage, vehicle speed and presence or absence of the vehicle accessory. Advantageously, this allows different moving average electrical power usages to be stored for different vehicle accessory configurations, improving the determined expected energy usage for each vehicle accessory configuration. This would prevent data from use of the vehicle with a vehicle accessory changing the moving averages for a solo vehicle, and also improve the accuracy of the expected energy usage when a vehicle accessory is attached. In examples, the memory and the one or more processors may be collectively configured to store and update predetermined average electrical power usages for a vehicle with multiple different vehicle accessories or types of vehicle accessories. For example, different predetermined average electrical power usages may be stored and updated for different types of trailers, roof attachments, and / or rear mounted accessories. Advantageously, more accurate expected energy usages may be provided for multiple different vehicle accessories or types of vehicle accessories. In examples, during driving, the memory and the one or more processors may be collectively configured to: receive a signal indicative of a vehicle acceleration, and update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a predetermined range of the vehicle acceleration. Advantageously, only data corresponding to a particular acceleration range (e.g., a low acceleration) is used to update the moving averages. In this way, the expected energy usages will be more accurate of steady-state driving, which may improve the overall accuracy of the expected energy usage. In examples, the predetermined range of the vehicle acceleration may be less than + / -0.5m / sA2, or less than + / -0.4m / sA2, or less than + / -0.3m / sA2, or less than + / -0.2m / sA2, or less than + / -0.1m / sA2. In examples, during driving, the memory and the one or more processors may be configured to update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a power usage less than a predetermined power limit. Advantageously, only data corresponding to a particular power usage range (e.g., a low power usage) is used to update the moving averages. In this way, the expected energy usages will be more accurate of steady-state driving, which may improve the overall accuracy of the expected energy usage. In particular, data from high power events (e.g., high acceleration or driving up a steep incline) may be excluded from the moving averages, improving the accuracy of the moving averages to steady-state driving. According to another aspect of the invention, there is provided a system comprising the control system described above and a sensor arranged to detect the electrical power usage of the electric drivetrain during driving of the vehicle, for example at one or more inverters of the electric drivetrain. Advantageously, detecting the electrical power usage of the electric drivetrain during driving provides a direct measurement of the power usage, improving the accuracy of the moving averages and expected energy usages. Detecting the electrical power usage at the inverter(s) ensures that the total electrical power usage of the drivetrain is considered. Additionally, other electrical consumers of the vehicle (e.g., an air conditioning system) are not included in the measured electrical power consumption so that the moving averages are reflective of the tractive energy of the drivetrain. In examples, the system may comprise a display configured to display one or more of: the expected vehicle range, the state of charge at a future time or location, and the energy usage of the future journey. Advantageously, the user (e.g., a driver) is provided with the information on the expected vehicle range, the state of charge at a future time or location, and the energy usage of the future journey. According to another aspect of the invention, there is provided a vehicle comprising the system or the control system described above. Advantageously, the moving average electrical power usages and expected energy usages are specific to the vehicle and its configuration, providing more accurate estimations of future energy usage for a future journey. According to another aspect of the invention, there is provided a method for estimating future energy usage of an electric drivetrain of a vehicle, the method comprising: storing a predetermined average electrical power usage for each of a plurality of discrete speed ranges, receiving a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle, receiving a signal indicative of a corresponding vehicle speed of the vehicle, updating the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges, in dependence on the moving average electrical power usages, determining an expected energy usage for a future journey and outputting a signal indicative thereof, and in dependence on the signal indicative of the expected energy usage, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. Advantageously, the moving average electrical power usages are thereby based on the actual use of the vehicle, and thus are adapted to the configuration of the vehicle. This may provide more accurate power usage data for estimating the future energy use of the vehicle, for example for a planned or expected journey. According to another aspect of the invention, there are provided computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform any method described herein. Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and / or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all embodiments and / or features of any embodiment can be combined in any way and / or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and / or incorporate any feature of any other claim although not originally claimed in that manner. BRIEF DESCRIPTION OF THE DRAWINGS One or more embodiments in accordance with the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 illustrates a vehicle; Figure 2A illustrates a control system and an electric drivetrain of the vehicle of FIG.1; Figure 2B illustrates the control system of FIG. 2; Figure 3 illustrates a flow diagram process for estimating future energy usage of the electric drivetrain of the vehicle, which control system is configured to perform; Figure 4 illustrates a first example memory of the control system for storing predetermined and / or moving averages of energy usage for discrete speed ranges; Figure 5 schematically illustrates updating the memory means of the control system; Figure 6 illustrates a flow diagram process for estimating future energy usage of the electric drivetrain of the vehicle, which a control system is configured to perform; Figure 7 schematically illustrates an example memory of the control system for storing predetermined and / or moving averages of energy usage for discrete speed ranges and for discrete road gradient ranges; Figure 8 schematically illustrates updating the memory means of the control system; Figure 9 illustrates a flow diagram process for determining and applying a correction to predetermined average electrical power usages; Figure 10 illustrates the application of a correction by the process of FIG. 9; Figure 11 illustrates a flow diagram of a process for determining a moving average electrical power usage; Figure 12 illustrates a flow diagram of a process for filtering received signals; and Figure 13 illustrates a flow diagram of a process for storing and determining average electrical power usages for a solo vehicle and for a vehicle with a vehicle accessory. DETAILED DESCRIPTION A vehicle 100 in accordance with an embodiment of the present invention is described herein with reference to the accompanying FIG. 1. The vehicle 100 has an electric drivetrain, and in particular the vehicle 100 may be an electric vehicle, a battery electric vehicle (BEV), or a hybrid vehicle (e.g., a plug-in hybrid vehicle or a mild hybrid vehicle). The electric drivetrain of the vehicle 100 may be a primary or secondary drivetrain for vehicle propulsion. The vehicle 100 includes a display device. The vehicle 100 may additionally include a user input device. The display device and / or the user input device may be located in the area of the vehicle driver so that the driver can see what is displayed on the display device and can provide an input via the user input device. The vehicle 100 may include an attachment point for a vehicle accessory, such as a trailer or a roof accessory or a rack accessory such as a rearmounted bicycle rack. The vehicle 100 may include a navigation system for planning a future journey and providing directions to the driver during the journey. Additionally or alternatively, the vehicle 100 may include a journey prediction system configured to predict a future journey of the vehicle 100. The future journey may be predicted based on past use of the vehicle 100, and may be further predicted based on the time, day, location and other factors that may be recorded during past use of the vehicle 100. The vehicle 100 comprises a control system 200 described below. FIG. 2A and FIG. 2B schematically illustrate the control system 200 in accordance with an embodiment of the present invention. The control system 200 is for estimating the future energy usage of an electric drivetrain of the vehicle 100. The control system 200 may be installed in the vehicle 100. The control system 200 may be operatively connected to an electric drivetrain 220 of the vehicle 100 and a display device 218 of the vehicle 100. The control system 200 may be operatively connected to the user input device, if provided. As shown in FIG. 2A, the electric drivetrain 220 includes an electric motor 202, which is coupled to one or more drive wheels for propelling the vehicle 100. The illustrated schematic shows a single electric motor 202 but it will be appreciated that there may be a plurality of electric motors 202, in particular two or four electric motors 202. The electric drivetrain 220 also includes a battery 206 for storing electrical energy, and an inverter 204 for inverting and regulating power received from the battery 206 and outputting it to the electric motors 202 during driving of the vehicle 100. A single inverter 204 is schematically illustrated, but it will be appreciated that the electric drivetrain 220 may include a plurality of inverters 204, for example an inverter 204 for each electric motor 202 or for each pair of electric motors 202. A sensor 210 may be provided on the inverter 204. The sensor 210 may be configured to detect an energy usage of the electric drivetrain 220 at the one or more inverters 204, in particular a tractive energy usage of the electric drivetrain 220. The sensor 210 may include more than one sensor. In alternative examples the or each inverter 204 may have an integrated sensor or other means for detecting the energy usage of the one or more inverters 204, and / or the vehicle 100 may comprise an energy management system configured to determine the energy usage of the electric drivetrain 220. It will be appreciated that the sensor 210 is arranged to detect the tractive energy use of the electric drivetrain 220, and does not measure energy use for any other energy consumer / element within the vehicle 100. The tractive energy use may be termed the vehicle tractive power consumption. The control system 200 also includes a controller 208, which is shown in more detail in FIG. 2B. The control system 200 comprises one controller 208, although it will be appreciated that this is merely illustrative and the control system 200 may include a plurality of controllers 208. The controller 208 comprises processing means 224 and memory means 226. The processing means 224 may be one or more electronic processing devices which operably execute computer-readable instructions. The memory means 226 may be one or more memory devices. The memory means 226 is electrically coupled to the processing means 224. The memory means 226 is configured to store instructions, and the processing means 224 is configured to access the memory means 226 and execute the instructions stored thereon. The control system 200, in particular the controller 208 and memory means 226, is configured to store a predetermined average electrical power usage for each of a plurality of discrete speed ranges, as described in more detail hereinafter with reference to FIG. 3. The stored predetermined average electrical power usages may be stored as an average energy usage per unit distance for each discrete speed range, for example in units of Wh / km. The control system 200 is configured to determine an expected energy usage for a future journey, for example a planned or predicted journey. The control system 200 determines the expected energy usage of the future journey based on the predetermined average energy usages stored in the memory means 226. The control system 200 is then configured to output an expected energy usage signal 216 indicative of the determined expected energy usage for the future journey. The determination of the expected energy usage of the future journey may be based on an average vehicle speed for the entire future journey, or the future journey may be divided into journey sections and the expected energy usage for each journey section may be determined. The determination of the expected energy usage of the future journey may be carried out by a navigation system or by a journey prediction system. The expected energy usage signal 216 is output to a display device 218. The expected energy usage signal 216 may be used to display one or more of an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. In examples, the state of charge at a future time or location comprises one or more of: a state of charge at the end of the future journey, or a state of charge at a time or location during the future journey. As explained further below, in some examples the predetermined average energy usages are stored in discrete speed ranges and in discrete road gradient ranges. In such examples, the expected energy usage of the future journey, and the corresponding expected energy usage signal 216, may be based on the stored predetermined average energy usages for both the discrete vehicle speed ranges and the discrete road gradient ranges. Thus, the control system 200 outputs the expected energy usage signal 216 based on the predetermined average energy usages. As explained further below, the control system 200 is configured to update the predetermined average energy usages stored in the memory means 226 based on data obtained while driving of the vehicle 100. In particular, the control system 200 is configured to update the predetermined average energy usages to moving average energy usages. Accordingly, after updating, the stored energy usage values are updated to reflect the specific configuration of the vehicle 100 and are more accurate to the specific vehicle 100, providing improved estimation of the expected energy usage for a future journey. The control system 200, in particular the controller 208, is configured to receive an energy usage signal 214 indicative of an energy usage of the electric drivetrain 220 during driving. The energy usage signal 214 may be indicative of a tractive power consumption. For example, as illustrated, the energy usage signal 214 may be received from the sensor 210 arranged to detect the energy usage of the electric drivetrain 220, or the energy usage signal 214 may be received from another part of the vehicle, for example an energy management system. In examples, the energy usage signal 214 is an instantaneous power usage of the electric drivetrain 220, in particular of the inverters 204. In particular, the energy usage signal 214 may be indicative of the instantaneous power usage of the electric drivetrain 220 in units of kW. The energy usage signal 214 may be received by the control system 200 at a sampling rate of between 100Hz and 10Hz. The controller 208 may be configured to convert the energy usage signal 214 into an energy usage per unit distance, in particular in units of Wh / km. The control system 200, in particular the controller 208, is also configured to receive a vehicle speed signal 212 indicative of the vehicle speed of the vehicle 100 corresponding to the received energy usage signal 214. The vehicle speed signal 212 may be received from a vehicle speed sensor 232 or from another part of the vehicle, for example a driving control system. The vehicle speed signal 212 may be received at the same sampling rate as the energy usage signal 214. The vehicle speed signal 212 is indicative of the vehicle speed in units of km / h. In some examples, as described further below, the control system 200, in particular the controller 208, is also configured to receive a road gradient signal 222 indicative of a road gradient corresponding to the received vehicle speed signal 212 and expected energy usage signal 216. The road gradient signal 222 may be received from a sensor 234, for example an inclinometer, or from another part of the vehicle, for example a driving control system. The road gradient signal 222 may be received at the same sampling rate as the energy usage signal 214 and the vehicle speed signal 212. The road gradient signal 222 is indicative of the road gradient in units of degrees or as a percentage indicating the vertical rise / decline per unit distance. The controller 208 is configured to update the stored predetermined average energy usage for each of the discrete speed ranges based on the received energy usage signal 214 and the received vehicle speed signal 212 and optionally also the received road gradient signal 222 to provide a moving average electrical power usage for each of the discrete speed ranges. After updating the predetermined values to the moving average values the control system 200, in particular the controller 208, is configured to determine an expected energy usage for a future journey based on the moving average electrical power usages and to output an expected energy usage signal 216. The expected energy usage signal 216 is used to display one or more of an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. Accordingly, after updating the predetermined average energy usages to the moving average electrical power usages the output expected energy usage signal 216 is more specific to the vehicle 100 and thereby provides improved accuracy of the expected energy usage for the future journey. The controller 208 comprises an input means 228 and an output means 230. The input means 228 may comprise an electrical input of the controller 208. The output means 230 may comprise an electrical output of the controller 208. The input means 228 is arranged to receive the vehicle speed signal 212, the energy usage signal 214 and optionally the road gradient signal 222. The vehicle speed signal 212 is an electrical signal which is indicative of the vehicle speed. The expected energy usage signal 216 is an electrical signal which is indicative of the energy usage of the electric drivetrain 220. The output means 230 is arranged to output the expected energy usage signal 216, which is indicative of the average energy usage of the electric drivetrain 220. The expected energy usage signal 216 may be provided to an output means such as a further controller or the display device 218 in the vehicle 100. FIG. 3 illustrates a flow diagram of the method 300 described above performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 300 according to an embodiment of the invention. The method 300 is a method for estimating future energy usage of the electric drivetrain 220 of the vehicle 100, such as the vehicle 100 illustrated in FIG. 1. The method 300 illustrated is performed for each of the discrete speed ranges. As illustrated, the method 300 comprises step 302 of storing a predetermined average electrical power usage for each of a plurality of discrete speed ranges. In particular, the method 300 comprises storing a predetermined average electrical power usage in the memory means 226 for each of a plurality of discrete speed ranges. The memory means 226 storing the predetermined average electrical power usage for each of a plurality of discrete speed ranges is schematically illustrated in FIG. 4. As illustrated, the memory means 226 stores a predetermined average electrical power usage for each of a first discrete speed range 402 to, in this example, a seventh discrete speed range 414. The vehicle speed 416 increases for each successive discrete speed range 402 to 414. The memory means 226 therefore stores the predetermined average electrical power usage for each of a plurality of discrete speed ranges 402 to 414 as a vector (a one dimensional matrix). In examples, each of the discrete speed ranges 402 to 414 may be equal in size (in terms of the range of speed covered). For example, each of the discrete speed ranges 402 to 414 may advance by between 10 km / h and 30 km / h. In other examples, the size of each of the discrete speed ranges 402 to 414 may be different. In one example, the first discrete speed range 402 may be Okm / h to 10km / h, the second discrete speed range 404 may be 10km / h to 30km / h, the third discrete speed range 406 may be 30km / h to 60km / h, the fourth discrete speed range 408 may be 60km / h to 10Okm / h, the fifth discrete speed range 410 may be 100km / h to 140km / h, the sixth discrete speed range 412 may be 140km / h to 160km / h, and the seventh discrete speed range 414 may be 160km / h to 240km / h. The predetermined average electrical power usage for each of the discrete speed ranges 402 to 414 may be determined by manufacturer vehicle testing (e.g., prior to sale of the vehicle or testing on a similar or identical vehicle, e.g., on a dyno), by modelling, and / or based on data from identical or similar vehicles already in use, such a fleet of identical or similar vehicles. The predetermined average electrical power usages for each of the discrete speed ranges 402 to 414 may thereby provide an estimate of the actual energy usage of the vehicle 100 when driving at a predicted speed. The predetermined average electrical power usages may be stored in units of Wh / km. Referring again to FIG. 3, in step 312 the method 300 comprises, in dependence on the predetermined average electrical power usages stored in the memory means 226, determining an expected energy usage for a future journey and outputting a signal indicative thereof. The determination of the expected energy usage of the future journey may be based on an average vehicle speed for the entire future journey, or the future journey may be divided into journey sections and the expected energy usage for each journey section may be determined. The output signal is the expected energy usage signal 216 described with reference to FIG. 2A and FIG. 2B. In step 314 the method 300 comprises, in dependence on the signal indicative of the expected energy usage generated in step 312, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. The displayed information is displayed on the display device 218 and presented to the driver. By steps 302, 312 and 314 the predetermined average electrical power usages are thereby used to determine an expected energy usage for a future journey and to display one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. As explained above, the method 300 further comprises updating the predetermined average electrical power usages stored in the memory means 226 based on data received during driving, in particular based on the received vehicle speed signal 212 and the energy usage signal 214 during driving. Accordingly, the method 300 further comprises step 304 of receiving a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle. In particular, the method 300 comprises receiving the energy usage signal 214 from the sensor 210 as described above. The method 300 further comprises step 306 of receiving a signal indicative of a corresponding vehicle speed of the vehicle. In particular, the method comprises receiving the vehicle speed signal 212 from the vehicle speed sensor 232 as described above. The method 300 comprises a threshold check 308 at which the number of data points of the received energy usage signal 214 and vehicle speed signal 212 are compared to a threshold number of data points. Before the threshold number of data points has been reached the method 300 uses the predetermined average electrical power usages in steps 312 and 314 to determine the expected energy usage and to display the one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. As shown in FIG. 3, at step 312 the predetermined average electrical power usages are retrieved from the memory means 226. After the threshold number of data points has been reached, the method 300 comprises step 310 of updating the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges. In examples, each of the moving average electrical power usages may be a simple moving average, a cumulative moving average, a weighted moving average, or an exponentially weighted moving average. Further description of the determination of the moving average electrical power usages is provided below. After step 310 of updating the stored predetermined average electrical power usage to a moving average electrical power usage, step 312 comprises determining an expected energy usage for a future journey based on the moving average electrical power usages as retrieved from the memory means 226. The determination of the expected energy usage of the future journey may be based on an average vehicle speed for the entire future journey, or the future journey may be divided into journey sections and the expected energy usage for each journey section may be determined. A signal indicative thereof is output, in particular the expected energy usage signal 216 described with reference to FIG. 2A and FIG. 2B. As above, in step 314 the method 300 then comprises, in dependence on the signal indicative of the expected energy usage, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. The displayed information is displayed on the display device 218 and presented to the driver. Therefore, for each of the plurality of discrete speed ranges, before the threshold number of data points has been received for the vehicle speed signal 212 and the energy usage signal 214 the method 300 uses the predetermined average electrical power usage to determine the expected energy usage for a future journey. Then, once the threshold number of data points has been reached, the method 300 comprises updating the predetermined average electrical power usage to a moving average electrical power usages and determining the expected energy usage for a future journey using the moving average. It will be appreciated that some of the discrete speed ranges will be updated from the predetermined average electrical power usage to the moving average electrical power usage sooner than others because the vehicle 100 will not be driven for equal amounts of time within all of the discrete speed ranges. Accordingly, the method 300 is performed for each of the discrete speed ranges and each of the discrete speed ranges is individually updated from the predetermined average electrical power usage to the moving average electrical power usage. This is schematically shown in FIG. 5, which shows the vector of average electrical energy usages stored in the memory means 226. As illustrated, initially the memory means 226 stores starting values 502 comprising the predetermined average electrical power usage for all of the discrete speed ranges. During initial collection of data (in particular receiving the energy usage signals and the vehicle speed signals) those data points are stored as first intermediate values 504 but the output signal from the memory means 226 is still the predetermined average electrical power usage. Once any one of the discrete speed ranges reaches the threshold number of data points the predetermined average electrical power usage for that discrete speed range is updated to the moving average electrical power usage and the corresponding output signal is then indicative of the moving average. As shown, in the illustrated second intermediate values 506 four of the discrete speed ranges have been updated. Eventually, once all of the discrete speed ranges reach the threshold number of data points the predetermined average electrical power usages are updated to the moving average electrical power usages to provide the illustrated moving average values 508, and the output signals from the memory means 226 are all indicative of the moving average. FIG. 6 illustrates a flow diagram of a further the method 600 that may be performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 600 according to an embodiment of the invention. The method 600 is a method for estimating future energy usage of the electric drivetrain 220 of the vehicle 100, such as the vehicle 100 illustrated in FIG. 1. The method 600 is similar to the method 300 and is performed for each of the discrete speed ranges. As illustrated, the method 600 comprises step 602 of storing a predetermined average electrical power usage for each of a plurality of discrete speed ranges. In particular, the method 600 comprises storing a predetermined average electrical power usage in the memory means 226 for each of a plurality of discrete speed ranges and for each of a plurality of discrete road gradient ranges. The memory means 226 storing the predetermined average electrical power usage for each of a plurality of discrete speed ranges at each of a range of discrete road gradients is schematically illustrated in FIG. 7. As illustrated, the memory means 226 stores a predetermined average electrical power usage for each of a first discrete speed range 702 to a seventh discrete speed range 714 and for each of a first discrete road gradient range 718 to a seventh discrete road gradient range 730. The vehicle speed 716 increases for each successive discrete speed range 702 to 714. The road gradient 732 increases or decreases for each successive road gradient range. The memory means 226 therefore stores a matrix of the predetermined average electrical power usage for each of a plurality of discrete speed ranges 702 to 714 and for each of the discrete road gradient ranges 718 to 730. In examples, each of the discrete speed ranges 702 to 714 may be equal in size (in terms of the range of speed covered). For example, each of the discrete speed ranges 702 to 714 may advance by between 10 km / h and 30 km / h. In other examples, the size of each of the discrete speed ranges 702 to 714 may be different. In one example, the first discrete speed range 702 may be Okm / h to 10km / h, the second discrete speed range 704 may be 10km / h to 30km / h, the third discrete speed range 706 may be 30km / h to 60km / h, the fourth discrete speed range 708 may be 60km / h to 10Okm / h, the fifth discrete speed range 710 may be 100km / h to 140km / h, the sixth discrete speed range 712 may be 140km / h to 160km / h, and the seventh discrete speed range 714 may be 160km / h to 240km / h. Similarly, each of the discrete road gradient ranges 718 to 730 may be equal in size (in terms of the degrees of road gradient). For example, each of the discrete road gradient ranges 718 to 730 may advance by between 1 degree (1.75%) and 5 degrees (5.24%), for example between 1 degree (1.75%) and 3 degrees (5.24%). In other examples, the size of each of the discrete road gradient ranges 718 to 730 may be different. The predetermined average electrical power usage for each of the discrete speed ranges 702 to 714 and each of the discrete road gradient ranges 718 to 730 may be determined by manufacturer vehicle testing (e.g., prior to sale of the vehicle or testing on a similar or identical vehicle, e.g., on a dyno), by modelling, and / or based on data from identical or similar vehicles already in use, such a fleet of identical or similar vehicles. The predetermined average electrical power usages for each of the discrete speed ranges 402 to 414 and each of the discrete road gradient ranges 718 to 730 may thereby provide an estimate of the actual energy usage of the vehicle 100 when driving at a predicted speed on a predicted road gradient. The predetermined average electrical power usages may be stored in units of Wh / km. Referring again to FIG. 6, in step 612 the method 600 comprises, in dependence on the predetermined average electrical power usages stored in the memory means 226, determining an expected energy usage for a future journey and outputting a signal indicative thereof. The determination of the expected energy usage of the future journey may be based on an average vehicle speed for the entire future journey, or the future journey may be divided into journey sections and the expected energy usage for each journey section may be determined. The output signal is the expected energy usage signal 216 described with reference to FIG. 2A and FIG. 2B. In step 614 the method 600 comprises, in dependence on the signal indicative of the expected energy usage generated in step 612, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. The displayed information is displayed on the display device 218 and presented to the driver. By steps 602, 612 and 614 the predetermined average electrical power usages are thereby used to determine the expected energy usage of the future journey and to display one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. In the same manner as method 300 described above, the method 600 further comprises updating the predetermined average electrical power usages stored in the memory means 226 based on data received during driving, in particular based on the received vehicle speed signal 212 and the energy usage signal 214 during driving. Accordingly, the method 600 further comprises step 604 of receiving a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle. In particular, the method 600 comprises receiving the energy usage signal 214 from the sensor 210 as described above. The method 600 further comprises step 606 of receiving a signal indicative of a corresponding vehicle speed of the vehicle. In particular, the method comprises receiving the vehicle speed signal 212 from the vehicle speed sensor 232 as described above. In this example, the method 600 comprises step 616 of receiving a signal indicative of a road gradient. In particular, the method comprises receiving the road gradient signal 222 from the sensor 234 as described above. The method 600 comprises a threshold check 608 at which the number of data points of the received energy usage signal 214, vehicle speed signal 212 and road gradient signal 222 are compared to a threshold number of data points. Before the threshold number of data points has been reached the method 600 uses the predetermined average electrical power usages in steps 312 and 314 to determine the expected energy usage and to display the one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. As shown in FIG. 6, at step 612 the predetermined average electrical power usages are retrieved from the memory means 226. After the threshold number of data points has been reached, the method 600 comprises step 610 of updating the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges and each of the plurality of discrete road gradient ranges based on the received signals indicative of the electrical power usage, vehicle speed and road gradient to provide a moving average electrical power usage for each of the plurality of discrete speed ranges and road gradient ranges. In examples, each of the moving average electrical power usages may be a simple moving average, a cumulative moving average, a weighted moving average, or an exponentially weighted moving average. Further description of the determination of the moving average electrical power usages is provided below. After step 610 of updating the stored predetermined average electrical power usage to a moving average electrical power usage, step 612 comprises determining an expected energy usage for a future journey based on the moving average electrical power usages as retrieved from the memory means 226. The determination of the expected energy usage of the future journey may be based on an average vehicle speed and average gradient for the entire future journey, or the future journey may be divided into journey sections and the expected energy usage for each journey section may be determined. A signal indicative thereof is output, in particular the expected energy usage signal 216 described with reference to FIG. 2A and FIG. 2B. As above, in step 614 the method 600 then comprises, in dependence on the signal indicative of the expected energy usage, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey. The displayed information is displayed on the display device 218 and presented to the driver. Therefore, for each of the plurality of discrete speed ranges and road gradient ranges, before the threshold number of data points has been received for the vehicle speed signal 212, the energy usage signal 214 and the road gradient signal 222 the method 600 uses the predetermined average electrical power usage to determine the expected energy usage for a future journey. Then, once the threshold number of data points has been reached, the method 600 comprises updating the predetermined average electrical power usage to the moving average electrical power usage and determining the expected energy usage for a future journey using the moving average. It will be appreciated that some of the discrete speed ranges and discrete road gradient ranges will be updated from the predetermined average electrical power usage to the moving average electrical power usage sooner than others because the vehicle 100 won't be driven for equal amounts of time within all of the discrete speed ranges and all the discrete road gradient ranges. Accordingly, the method 600 is performed for each of the discrete speed ranges and each of the discrete road gradient ranges, and each of the discrete speed ranges and road gradient ranges is individually updated from the predetermined average electrical power usage to the moving average electrical power usage. This is schematically shown in FIG. 8, which shows a matrix of average power usages stored in the memory means 226. As illustrated, initially the memory means 226 stores starting values 802 comprising the predetermined average electrical power usage for all of the discrete speed ranges and discrete road gradient ranges. During initial collection of data (in particular receiving the energy usage signals and the vehicle speed signals) those data points are stored as first intermediate values 804 but the output signal from the memory means 226 is still the predetermined average electrical power usage. Once any one of the discrete speed ranges and discrete road gradient ranges reaches the threshold number of data points the predetermined average electrical power usage is updated to the moving average electrical power usage and the output signal from the memory means 226 is then indicative of the moving average. As shown, in the illustrated second intermediate values 806 several of the discrete speed ranges and discrete gradient ranges have been updated. Eventually, once all of the discrete speed ranges and discrete gradient ranges reach the threshold number of data points the predetermined average electrical power usages are updated to the moving average electrical power usages to provide the illustrated moving average values 808, which are output from the memory means 226. As explained above, for each discrete speed range 402 to 414, 702 to 714 (and optionally also for each discrete road gradient range 718 to 730), the method 300, 600 comprises updating the predetermined average electrical power usages to moving average electrical power usages after a threshold number of data points has been reached. However, that will not happen simultaneously for all discrete speed ranges 402 to 414, 702 to 714 (or all discrete road gradient ranges 718 to 730). FIG. 9 illustrates a flow diagram of a further the method 900 that may be performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 900 according to an embodiment of the invention. The method 900 is a method for applying a correction to the predetermined average electrical power usage of one of the plurality of discrete speed ranges based on the moving average of another of the plurality of discrete speed ranges. In step 902 the method 900 comprises determining the moving average of a first of the plurality of discrete speed ranges based on at least a threshold number of data points, in the same manner as described above. In step 904 the method 900 comprises determining a difference between the predetermined average electrical power usage and the moving average electrical power usage for the first discrete speed range. In step 906 the method 900 comprises applying a correction to the predetermined average electrical power usage of a second discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached. The correction is based on the determined difference from step 904. Accordingly, after one of the discrete speed ranges has a moving average based on at least the threshold number of data points, the predetermined average electrical power usage of other discrete speed ranges can be updated based on the difference between that moving average and the original predetermined average electrical power usage. In another example, step 902 comprises determining the moving average of a plurality of the plurality of discrete speed ranges based on at least a threshold number of data points for the plurality of discrete speed ranges. In this example, step 904 comprises determining an average difference between the predetermined average electrical power usages and the moving average electrical power usages for the plurality of discrete speed ranges with moving averages as per step 902. In this example, step 906 comprises applying a correction to the predetermined average electrical power usage of at least one other discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached. The correction is based on the determined average difference determined in step 904. FIG. 10 illustrates application of a correction as described with reference to FIG. 9. FIG. 10 shows a graph 1000 illustrating the predetermined average electrical power usages 1002 plotted against a vertical axis of power and a horizontal axis of vehicle speed. In this example, one of the discrete speed ranges has been updated to the moving average electrical power usage 1006 as illustrated. Based on a difference between the moving average electrical power usage 1006 and the corresponding predetermined electrical power usage for that discrete speed range, the other discrete speed ranges have been corrected to the updated predetermined average electrical power usages 1004 as illustrated. In this example, the updated predetermined average electrical power usages 1004 are higher than the predetermined average electrical power usages 1002. Accordingly, the method 900 improves the accuracy of the predetermined average electrical power usages for all of the discrete speed ranges even before the threshold number of data points has been reached for all of the discrete speed ranges. FIG. 11 illustrates a flow diagram of a further method 1100 that may be performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 1100 according to an embodiment of the invention. The method 1100 is a method for determining the moving average electrical power usages as described above. In particular, steps 310 and 610 of the methods 300, 600 comprise determining a moving average electrical power usage and may be performed using the method 1100. As described above, the controller 208 is configured to receive the vehicle speed signal 212, the energy usage signal 214 and optionally the road gradient signal 222, and to update the predetermined average energy usage values to moving average values for each of the plurality of discrete speed ranges and optionally also for each of the plurality of discrete road gradient ranges. In the example of FIG. 11 the method comprises step 1102 of receiving the vehicle speed signal 212, the energy usage signal 214 and optionally the road gradient signal 222. This corresponds to method steps 304, 306, 604, 606 and 616 as described above. For each discrete speed range (and optionally for each discrete road gradient range), the method 1100 also includes step 1104 of determining a first moving average electrical power usages from a plurality of data sets, each data set having a first predetermined number of data points of the vehicle speed signal 212 the energy usage signal 214 and optionally the road gradient signal 222. After the first moving average of step 1104 is based on a threshold number of data sets, step 1106 comprises determining a second moving average electrical power usage from the first moving average electrical power usage and subsequent data sets. In some examples, the stored predetermined average energy usage is updated with the second moving average electrical power usage in step 1110. In particular, steps 310, 610 of method 300 and method 600 may use the second moving average electrical power usage. Advantageously, this reduces the amount of data that needs to be stored to determine the moving average, and may also reduce the volatility of the moving average that is used to determine the expected energy usage of the future journey. In addition, the first and second moving averages can be stored in RAM on the vehicle and so can be stored during interruptions from driving (and data collection). Accordingly, it is possible to capture and use data from short drives that would usually not generate enough data to result in an updated first and / or second moving average. In other examples, after the second moving average of step 1106 is based on a threshold number of data sets, the method 1100 may include step 1108 of determining a third moving average electrical power usage from the second moving average electrical power usage and subsequent data sets. In some examples, the stored predetermined average energy usage is updated with the third moving average electrical power usage in step 1110. In particular, steps 310, 610 of method 300 and method 600 may use the third moving average electrical power usage. Advantageously, this reduces the amount of data that needs to be stored to determine the moving average, and may also reduce the volatility of the moving average that is used to determine the expected energy usage of the future journey. In addition, the first, second and third moving averages can be stored in RAM on the vehicle and so can be stored during interruptions from driving (and data collection). Accordingly, it is possible to capture and use data from short drives that would usually not generate enough data to result in an updated first and / or second and / or third moving average. It will be appreciated that this is a form of cumulative moving average. In other examples, the or each moving average may be a simple moving average, a weighted moving average, or an exponentially weighted moving average. FIG. 12 illustrates a flow diagram of a further method 1200 that may be performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 1200 according to an embodiment of the invention. The method 1200 is a method for updating the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges (and optionally for each of the discrete road gradient ranges) using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a predetermined range of vehicle acceleration and / or electrical power usage. Step 1202 of method 1200 comprises receiving the energy usage signal 214. Step 1202 corresponds to steps 304 and 606 as described above with reference to FIG. 3 and FIG. 6. In some examples, step 1202 also includes receiving the road gradient signal 222, which may correspond to step 616 of the method described with reference to FIG. 6 but may also apply to the method 300 of FIG. 3. In some examples, step 1202 further comprises receiving a signal indicative of an acceleration of the vehicle. In examples, the control system 200 may directly receive a signal indicative of the acceleration of the vehicle, or it may receive the vehicle speed signal 212 and determine the acceleration from the vehicle speed signal 212. In one example, step 1204 of method 1200 comprises comparing the energy usage signal 214 to a limit, and step 1206 comprises only using the energy usage signal 214 to determine the moving average electrical power usage if the energy usage signal 214 is less than the limit. In this way, data associated with particularly high (or low) energy usage (for example when accelerating the vehicle up an incline) is not used when determining the moving average electrical power usage. In some examples the energy usage signal 214 is compared against an instantaneous electrical power limit (i.e., in kW), and in other examples it is compared against an electrical power rate limit (e.g., in kW / hA2). In another example, step 1204 of method 1200 comprises comparing the acceleration of the vehicle 100 to a predetermined range or limit, and step 1206 comprises only using the corresponding energy usage signal 214 to determine the moving average electrical power usage if the acceleration is within the predetermined range or less than the limit. In this way, data associated with particularly strong acceleration (or deceleration) is not used when determining the moving average electrical power usage). In another example, step 1204 of method 1200 comprises comparing the road gradient signal 222 to a predetermined range, and step 1206 comprises only using the corresponding energy usage signal 214 to determine the moving average electrical power usage if the road gradient signal 222 is within the predetermined range. In this way, data associated with particularly steep gradients (positive or negative, for example when driving the vehicle up or down a steep incline) is not used when determining the moving average electrical power usage. In one example, only data associated with a (substantially) flat road gradient is used to determine the moving average electrical power usage. The method 1200 may be performed between step 306 and threshold check 308 in the method of FIG. 3, or between step 616 and threshold check 608 in the method 600 illustrated in FIG. 6. Accordingly, method 1200 is a method of filtering out extreme values of the received energy usage signal 214, which may help to reduce volatility of the determined moving average electrical power usages. FIG. 13 illustrates a flow diagram of a further method 1300 that may be performed by the control system 200. In particular, the memory means 226 may comprise computer-readable instructions which, when executed by the processing means 224, perform the method 1300 according to an embodiment of the invention. The method 1300 is a method for storing and updating predetermined average electrical power usages for a plurality of discrete speed ranges for a solo vehicle and for a vehicle with a vehicle accessory, for example a trailer. Step 1302 of method 1300 is similar to step 302 of the method 300 f FIG. 3, and step 602 of the method 600 of FIG. 6, and comprises storing predetermined average electrical power usages for the plurality of discrete speed ranges for a solo vehicle, and storing predetermined average electrical power usages for the plurality of discrete speed ranges for a vehicle with a vehicle accessory, for example a trailer. In this context, a solo vehicle is a vehicle without a vehicle accessory. In particular, step 1302 of the method 1300 comprises storing predetermined average electrical power usages for a solo vehicle and a vehicle with a vehicle accessory in the memory means 226 for each of the plurality of discrete speed ranges, and optionally also for each of the plurality of discrete road gradient ranges. Accordingly, the predetermined average electrical power usages for a solo vehicle and a vehicle with a vehicle accessory are stored in separate vectors or matrices similar to those illustrated in FIG. 4 and FIG. 7. In addition, predetermined average electrical power usages for a vehicle with different types of accessories may be stored separately. I n examples, step 1302 of the method 1300 comprises storing predetermined average electrical power usages for a vehicle with a plurality of different vehicle accessories, for example different types of trailers, or roof attachments, or rack attachments. Step 1304 comprises receiving a signal indicative of the presence or absence of a vehicle accessory. For example, step 1304 may comprise receiving a signal indicative of there being no vehicle accessory, or indicative of a solo vehicle configuration. Alternatively, step 1304 may comprise receiving a signal indicative of the presence of a vehicle accessory, and optionally also the type of vehicle accessory. The signal received at step 1304 may be provided from a user input device 1308, for example an HMI (e.g., touchscreen) where the driver can select whether a vehicle accessory is being used, and optionally also the type of vehicle accessory. Step 1306 of method 1300 comprises the remainder of the method 300 or the method 600 in which the predetermined average electrical power usages stored in step 1302 are updated to moving averages for the solo vehicle and for the vehicle with a vehicle accessory during driving in dependence on the signal received at step 1304. Accordingly, the method 1300 provides for separately storing predetermined average electrical power usages for a solo vehicle and a vehicle with a vehicle accessory, and so the expected energy usage of the future journey is improved by knowing of the presence or absence of a vehicle accessory and by storing different predetermined and moving average electrical power usages for a solo vehicle and a vehicle with a vehicle accessory (and optionally type of vehicle accessory). It will be appreciated that various changes and modifications can be made to the present invention without departing from the scope of the present application.

Claims

1. A control system for estimating future energy usage of an electric drivetrain of a vehicle, the control system comprising a memory and one or more processors collectively configured to:store a predetermined average electrical power usage for each of a plurality of discrete speed ranges,receive a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle,receive a signal indicative of a corresponding vehicle speed of the vehicle,update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges,in dependence on the moving average electrical power usages, determine an expected energy usage for a future journey and output a signal indicative thereof, and in dependence on the signal indicative of the expected energy usage, display one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey.

2. The control system of claim 1, wherein the future journey comprises a plurality of journey sections, each having a predicted vehicle speed,and wherein the memory and the one or more processors are collectively configured to determine the expected energy usage of the electric drivetrain for each journey section based on the moving average electrical power usage for the discrete speed range corresponding to each predicted vehicle speed of each journey section.

3. The control system of claim 1 or 2, wherein, for each discrete speed range, the memory and the one or more processors are collectivelyconfigured to update the predetermined average electrical power usage to the moving average electrical power usage once the moving average electrical power usage is based on a threshold number of data points.

4. The control system of claim 3, wherein, after updating the stored predetermined average electrical power usage to the moving averageelectrical power usage for a first discrete speed range of the plurality of discrete speed ranges, the memory and the one or more processors are collectively configured to:determine a difference between the predetermined average electrical power usage and the moving average electrical power usage for the first discrete speed range, andbased on the determined difference, apply a correction to the predetermined average electrical power usage of a second discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached.

5. The control system of claim 3 or 4, wherein, after the threshold number of data points has been reached for a first discrete speed rangeand a second discrete speed range and updating the stored predetermined average electrical power usage to the moving average electrical power usage for the first discrete speed range and the second discrete speed range of the plurality of discrete speed ranges, the memory and the one or more processors are collectively configured to:determine an average difference between the predetermined average electrical power usages and the moving average electrical power usages for the first discrete speed range and the second discrete speed ranges, andbased on the determined difference, apply a correction to the predetermined average electrical power usage of at least one further discrete speed range of the plurality of discrete speed ranges in which the threshold number of data points has not been reached.

6. The control system of any one of claims 1 to 5, wherein the memory and one or more processors are collectively configured to:determine a plurality of first moving average electrical power usages from a plurality of first data sets, each first data set having a first predetermined number of data points of the signals indicative of the received electrical power usage and the corresponding vehicle speed, and determine a second moving average electrical power usage from the plurality of first moving average electrical power usages.

7. The control system of any one of claims 1 to 6, wherein, during driving of the vehicle, the memory and the one or more processors arecollectively configured to receive a signal indicative of a road gradient corresponding to the received signals indicative of the electrical power usage and the vehicle speed.

8. The control system of claim 7, wherein the memory and the one or more processors are collectively configured to update the storedpredetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a predetermined range of the road gradient.

9. The control system of claim 7, wherein the memory and the one or more processors are collectively configured to:store a predetermined average electrical power usage for each of the plurality of discrete speed ranges and for each of a plurality of discrete road gradient ranges,update the stored predetermined average electrical power usages for each of the plurality of discrete speed ranges and each of the discrete road gradient ranges based on the received signals indicative of the electrical power usage, vehicle speed and road gradient to provide a moving average electrical power usage for each of the plurality of discrete speed ranges and for each of the plurality of discrete road gradient ranges.

10. The control system of any one of claims 1 to 9, wherein the memory and the one or more processors are collectively configured to: store predetermined average electrical power usages for the plurality of discrete speed ranges for a solo vehicle, store predetermined average electrical power usages for the plurality of discrete speed ranges for a vehicle with a vehicle accessory, receive a signal indicative of the presence or absence of the vehicle accessory, andupdate the stored predetermined average electrical power usages for the solo vehicle and the vehicle with the accessory based on the received signals indicative of the electrical power usage, vehicle speed and presence or absence of the vehicle accessory.

11. The control system of any one of claims 1 to 10, wherein, during driving, the memory and the one or more processors are collectively configured to:receive a signal indicative of a vehicle acceleration, and update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a predetermined range of the vehicle acceleration.

12. The control system of any one of claims 1 to 11, wherein, during driving, the memory and the one or more processors are configured to update the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges using only the received signals indicative of the electrical power usage and the vehicle speed that correspond to a power usage less than a predetermined power limit.

13. A system comprising the control system of any of claim 1 to claim 12 and a sensor arranged to detect the electrical power usage of the electric drivetrain during driving of the vehicle, optionally at one or more inverters of the electric drivetrain.

14. A vehicle comprising the system of claim 13 or the control system of any of claim 1 to claim 12.

15. A method for estimating future energy usage of an electric drivetrain of a vehicle, the method comprising:storing a predetermined average electrical power usage for each of a plurality of discrete speed ranges, receiving a signal indicative of an electrical power usage of the electric drivetrain during driving of the vehicle, receiving a signal indicative of a corresponding vehicle speed of the vehicle, updating the stored predetermined average electrical power usage for each of the plurality of discrete speed ranges based on the received signals indicative of the electrical power usage and the vehicle speed to provide a moving average electrical power usage for each of the plurality of discrete speed ranges,in dependence on the moving average electrical power usages, determining an expected energy usage for a future journey and outputting a signal indicative thereof, and in dependence on the signal indicative of the expected energy usage, displaying one or more of: an expected vehicle range, a state of charge at a future time or location, and an energy usage of the future journey.s

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