TECHNICAL FIELD

The invention relates to a system and a method and an arrangement arranged to estimate energy usage of alternative powertrains available to a predetermined vehicle, which system comprises a mobile communications device arranged to exchange data with a remote server. The invention can be applied in heavy-duty and commercial vehicles, such as trucks, buses and construction equipment. Although the invention will be described with respect to a commercial vehicle, the invention is not restricted to this particular vehicle, but may also be used in other vehicles such as passenger vehicles.

BACKGROUND

In conventional powertrains all propulsive energy is produced by an internal combustion engine. Comparing the fuel consumption for vehicles with conventional powertrains is relatively straightforward, using data relating to fuel consumption over a set distance for a predetermined driving cycle. However, for hybrid powertrains, the fuel consumption is reduced by regeneration of kinetic and potential energy. In the case of full electric powertrains, all propulsion energy is supplied by a battery that is charged from the grid while the vehicle is standing still. Plugin hybrid vehicles use energy both from an internal combustion engine and the electric grid. Driving cycles for vehicles with hybrid and electric powertrains can differ from those used for vehicles with conventional powertrains.

A driving cycle is a series of data points representing the speed of a vehicle versus time. Driving cycles are produced by different countries and organizations to assess the performance of vehicles in various ways, as for example fuel consumption and polluting emissions (HC, C0 ₂ , etc.) for conventional powertrains. In the latter case, Fuel consumption and emission tests are performed on chassis dynamometers. Tailpipe emissions are collected and measured to indicate the performance of the vehicle.

A common use for driving cycles is in vehicle simulations. More specifically, driving cycles are used in propulsion system simulations to predict performance of internal combustion engines, transmissions, electric drive systems, batteries, fuel cell systems, and similar components. Some driving cycles are derived theoretically, as it is preferred in the European Union, whereas others are derived by direct measurements of a driving pattern deemed representative for normal use of the vehicle. To complicate things further, there are two types of driving cycles, namely Transient driving cycles and Modal driving cycles. Transient driving cycles involve many changes, representing the constant speed changes typical of on-road driving, while modal driving cycles involve protracted periods at constant speeds. Examples of transient driving cycles are the American FTP-75 and the unofficial European Hyzem driving cycles. Examples of modal driving cycles are the Japanese 10-15 Mode and JC08 driving cycles. In addition, some transient driving cycles such as the official New European Driving Cycle (NEDC) are designed to fit particular emission requirement and bear little relation to real world driving patterns. On the other hand, the forthcoming Worldwide harmonized Light vehicles Test Procedures (WLTP) is attempting to mimic real word driving behavior. The most common driving cycles are probably the WLTP, NEDC and the FTP-75, the latter corresponding to urban driving conditions only.

Consequently, comparing the energy usage for vehicles with different kinds of powertrains can be a problem, especially as the standardized test cycles for each powertrain can vary. Also, the standard test cycles used can result in energy usage data that are difficult to replicate outside a test track. In addition, many standard test cycles are not adapted for light trucks, buses or other commercial vehicles. The consequence of the multiple powertrain types is that the selection, for example, of a specific transport vehicle or a public transportation vehicle, is complicated for a customer. The best selection can depend on how the vehicle is used. For example, an urban route involving many starts and stops, during the route, can favour hybrid technology. On the other hand, for a route involving both urban and extra-urban driving it can be difficult to determine whether a hybrid or a conventional powertrain should be selected.

A prior art method for performing road tests in order to select a suitable vehicle is disclosed in US201 1270486. According to this document, drive cycle data is collected from a test vehicle over a period of one or more weeks. The drive cycle data comprises telemetric and informational data regarding the test vehicle, including for example locational data and vehicle speed data, which can be based on GPS data, as well as mass data, and/or vehicle runtime information, which is derived from vehicle on-board diagnostics (OBD) system using a data logging tool. The user must also have access to an energy modelling tool linked to the server for calculating energy consumption for the vehicle in question once the data collection has been completed.

This is a cumbersome method that requires physical access to a vehicle over an extended period of time, as well as equipment for accessing the vehicle OBD system, a data logging tool, a data collecting server for handling large amounts of data, data models for the specific vehicle, and data models for performing the necessary output data. In real life, only vehicle manufactures or companies managing major fleets of vehicles will have the means and equipment to perform such tests.

The object of the invention is to provide a system that facilitates the comparison of the energy usage for a vehicle which can be supplied with different types of powertrains and solves the above problems. A further object is to enable a user to perform a comparison in real-time, without requiring access to any on-board sensors or systems in the vehicle.

SUMMARY

The above problems have been solved by a system and a method as claimed in the appended claims.

According to a preferred embodiment, the invention relates to a system arranged to estimate energy usage of alternative powertrains available to a predetermined first vehicle, which system comprises a mobile communications device arranged to exchange data with a remote server. The mobile communications can be a mobile phone, a tablet computer, or a similar portable mobile communications device able to download an application, hereinafter termed "app", from the internet, a cloud based service, or similar. In the subsequent text it is assumed that the mobile communications has the required program or app installed. The app is preferably, but not necessarily, started by a user intending to estimate energy usage using the system. The mobile communications device is arranged to receive position data and time, i.e. a time stamp for the actual position, from the Global Positioning System, commonly termed GPS, during travelling a route with a second vehicle. The GPS is a space-based satellite navigation system that provides location (position coordinates, altitude data, etc.) and time information for that location in all weather conditions, anywhere on or near the earth where there is an unobstructed line of sight to four or more GPS satellites. In addition to GPS, other suitable systems include the Russian Global Navigation Satellite System (GLONASS), the Indian Regional Navigation Satellite System, and the Chinese Bei Dou Navigation Satellite System, as well as the planned European Union Galileo positioning system.

The mobile communications device is located in a second vehicle (not necessarily of the same type as the predetermined first vehicle) and is arranged to transmit data comprising multiple sets of at least position data and time to the remote server. Sets of data to be transmitted is collected continuously or at regular, predetermined intervals which can be selected depending on the desired accuracy of the energy usage estimation. The data capture rate for most vehicles may be at least 2 Hz but can be any frequency based on the desired accuracy and technological capabilities of the system. The capture rate can also be selected to limit the amount of data transmitted.

Data collection and transmission can be initiated and terminated at any time by a user operating the mobile communications device. Alternatively, data can be collected and transmitted between predetermined starting and finishing points along a route travelled by the second vehicle.

Examples of additional data available to the mobile communications device can be, for instance, accelerometer data or atmospheric pressure from sensors provided in the mobile communications device. If desired, such data can be included in the sets of data transmitted to the server.

The remote server is arranged to determine a road profile and a speed profile for a route travelled by the second vehicle, based on the received data and altitude related data. In this context, the road profile describes variations in altitude along the route travelled by the vehicle, while the speed profile describes variations in vehicle speed, including accelerations and decelerations, along this route. The provision of altitude related data will be described in further detail below.

The remote server is arranged to estimate energy usage data for each of a number of predetermined alternative powertrains for the route travelled by the second vehicle, based on the determined road and speed profiles. A mathematical model of each powertrain can be used for these calculations. Preferably, one model is provided for every alternative powertrain variant analysed and modelled. As indicated above, the estimation is performed for alternative powertrains available to the predetermined first vehicle or model of the first vehicle. For instance, a particular vehicle can be provided with one of a number of alternative powertrains during assembly. Non-limiting examples of alternative powertrains are conventional, micro hybrid, hybrid, plugin-in hybrid, and full electric powertrains.

In a conventional powertrain all propulsion energy is produced in the engine using fossil fuel, e.g. diesel, LNG, CNG, or biofuel, e.g. ethanol, RME. No energy regeneration is possible. In a micro hybrid powertrain, fuel consumption is reduced by avoiding engine idling, for instance by start-stop operation. In a hybrid powertrain fuel consumption is reduced by regeneration of kinetic and potential energy, for instance, using a motor/generator when coasting or when travelling downhill. In a plugin-in hybrid vehicle fuel consumption is reduced by brake energy regeneration and by charging. Charging means that an on-board battery is charged from the grid while the vehicle is standing still, and possible by using a relative small capacity combustion engine driving a generator when the vehicle is moving. In a Full electric powertrain, all propulsion energy is drawn from a battery that is charged from an electric grid while the vehicle is standing still. Energy consumption is reduced by brake energy regeneration.

The mobile communications device is arranged to display estimated energy usage data for each alternative powertrain received from the remote server. In this way, the invention can be used for assisting a user in selecting a powertrain that best suits the user's requirements before purchasing, leasing, or renting a vehicle. The displayed energy usage data provides a simple and educational way of demonstrating which alternative is the most fuel efficient or has the least environmental impact. According to the invention the system is arranged to perform necessary data acquisition before the energy usage can be determined and displayed to the user. The data acquisition is initiated when the user starts the app and is terminated when the user stops the app. Preferably, as much as possible, if not all, of the data acquisition is performed by the mobile communications device. As indicated above, the remote server requires altitude related data in addition to the received time stamp and position data to determine a road profile and a speed profile for a route travelled by the second vehicle. The altitude related data can be determined in a number of different ways from available data or signals. According to a first example, the mobile communications device can be arranged to calculate an altitude for each position using the GPS data and transmit altitude related data to the remote server. A GPS receiver can determine the altitude by trilateration, preferably with signals from four or more satellites. According to a second example, the mobile communications device is arranged to calculate an altitude for each position using a signal from an internal pressure sensor that can detect changes in atmospheric pressure, or from an accelerometer that can detect positional changes of the device. The arrangements for determining altitude related data can be used singly or be used in any suitable combination for improved accuracy.

The calculated altitude related data for each position is then transmitted to the remote server. The altitude determined according to these examples may not be very exact, but is sufficiently accurate for calculating road slopes in order to determine a road profile. According to a third example, the remote server is arranged to retrieve altitude related data for each position from a database. Such a database can be provided by a supplier or contained stored data from vehicles having travelled the same route on earlier occasions. The database can be stored on the remote server or in any other suitable location from which the data can be retrieved. Theoretically, the database could be stored in the mobile communications device, but this may not be practical with respect to the data storage capacity required.

The remote server is arranged to determine a road profile comprising road slope for each position, wherein road slope is determined as a function of calculated speed and altitude data. At the same time, the remote server is arranged to determine a speed profile, where after acceleration and deceleration is determined as a function of speed variation over time. Acceleration is implicitly derived from the speed profile by numerically calculating the time derivate of the estimated speed. Using the determined road and speed profiles and acceleration, propulsion power can be estimated as a function of road slope, speed and acceleration. Energy usage data such as fuel and/or electrical energy consumption is calculated by combining propulsion power with a mathematical model of each powertrain. There is one model for every powertrain variant to be analysed. The remote server is arranged to estimate energy usage data simultaneously for at least two predetermined alternative powertrains selected by a user. The at least two predetermined alternative powertrains are selectable from a list of powertrains for type or model of the predetermined first vehicle. The list of powertrains can be downloaded to the mobile communications device with the app or be supplied from the remote server when the app is started. According to one example, the system is arranged to estimate the energy usage for a predetermined vehicle. In this case the user only needs to indicate which powertrains to compare for this vehicle. Alternatively at least two predetermined alternative powertrains are selectable for any one of a predetermined vehicle type or model selected by a user. In this case the user must first select a vehicle type or model from a list of vehicles or models downloaded to the mobile communications device with the app or be supplied from the remote server when the app is started. Subsequently, alternative powertrains available for the selected vehicle or model can be selected from a list of powertrains. As indicated above, examples of alternative powertrains can be conventional (fossil fuel or biofuel), micro hybrid, hybrid, plugin-in hybrid, and full electric powertrains.

The mobile communications device is arranged to display estimated energy usage data comprising one or more of fuel consumption, electric energy usage, regenerated energy, and/or emitted C0 ₂ nitrous oxides (NO _x ) and other emissions. The displayed data can vary depending on desired parameters selected for display by the user and/or the types of powertrain selected. The mobile communications device can be arranged to display the estimated energy usage data in real time, that is, the remote server can be arranged to perform the calculation while the mobile communications device is travelling along the route with the second vehicle and the displayed estimated energy usage data can be updated while travelling along the route. A further advantage with a real time update is that the app can be used also as a support to learn how to drive more efficiently. Alternatively the calculation and display of the estimated energy usage data can be performed directly after the user of the mobile communications device indicates that the end of the route has been reached.

The invention further relates to a method for estimating energy usage of alternative powertrains in a predetermined first vehicle, wherein a mobile communications device arranged to exchange data with a remote server. The method comprises the steps of;

- receiving position data and time, e.g. a time stamp, from a GPS system using the mobile communications device during travelling a route with a second vehicle and transmitting multiple sets of at least position data and time to the remote server;

- determining a road profile and a speed profile for a route travelled by the second vehicle using the remote server, based on the received data and altitude related data;

- estimating energy usage data for each of a number of predetermined alternative powertrains for the route travelled by the second vehicle using the remote server, based on the determined road and speed profiles; and

- transmitting energy usage data from the remote server to the mobile communications device and displaying the estimated energy usage data for each alternative powertrain.

The remote server requires altitude related data in addition to the received time stamp and position data to determine a road profile and a speed profile for a route travelled by the second vehicle.

According to a first example, the method involves calculating an altitude for each position in the mobile communications device using GPS data and transmitting altitude related data to the remote server. According to a second example, the method involves calculating an altitude for each position in the mobile communications device using a pressure sensor in the device and transmitting altitude related data to the remote server. According to a first example, the method involves retrieving altitude related data for each position from a database accessible to the remote server. The database can be stored in the remote server, in the mobile communications device or in a similar suitable location. The method further involves determining a road profile comprising road slope for each position, wherein road slope is determined as a function of calculated speed and altitude related data. Subsequently the method determines a speed profile, wherein acceleration and deceleration is determined by calculating the time derivate of the calculated speed. Acceleration is implicitly derived from the speed profile by numerically calculating the time derivate of the estimated speed. Using the determined road and speed profiles and acceleration, propulsion power can be estimated as a function of road slope, speed and acceleration. Energy usage data such as fuel and/or electrical energy consumption is calculated by combining propulsion power with a mathematical model of each powertrain. There is one model for every powertrain variant to be analysed. The remote server is arranged to estimate energy usage data simultaneously for at least two predetermined alternative powertrains selected by a user.

According to the invention the method allows selection of at least two predetermined alternative powertrains from a list of powertrains for a predetermined vehicle type or model of the predetermined first vehicle. Alternatively at least two predetermined alternative powertrains can be selected for any one of a predetermined vehicle type or model selected by a user in a previous step.

When the user terminates the data acquisition by stopping the app, and the necessary calculations have been performed, the estimated energy usage data comprising one or more of fuel consumption, electric energy usage, regenerated energy, and/or emitted C0 ₂ or NOx for the selected powertrains is displayed on the mobile communications device. As mentioned above the estimated energy usage data can be displayed in real time and updated while travelling the route. The invention also relates to a computer program comprising program code means for performing all the steps of the above method when said program is run on a computer.

The invention further relates to a computer program product comprising program code means stored on a computer readable medium for performing all steps of the above method when said program product is run on a computer. Finally, the invention relates to a storage medium, such as a computer memory or a nonvolatile data storage medium, for use in a computing environment, the memory comprising a computer readable program code to perform the above method.

An advantage of the inventive idea is that a user, for instance a prospective customer, can enter a vehicle as a passenger and start the application on a mobile communications device. At an initial position the route evaluation can be started when the user executes a command to start the evaluation in the application. When reaching a desired end position a command to stop the evaluation is executed. After this command the results representing energy usage, such as fuel consumption electric energy usage, regenerated energy, and/or emitted C0 ₂ /NOx for the selected powertrains, from the route analysis is immediately presented on the mobile communications device.

A further advantage of the system is that it does not require access to the vehicle systems, such as sensors or the OBD system, or logging of large amounts of vehicle related data. According to the invention, a basic version of the inventive system only requires GPS data, that is, location and a time stamp, in order to perform the necessary calculations. The amounts of data transmitted to a remote server can therefore be kept to a minimum.

Using the inventive system, it is possible for a customer to evaluate vehicles in real-time and in real world operation. The system, realized as a user friendly application in a mobile communications device, e.g. a smart phone, a tablet or similar, evaluates a route in such a way the selection among the previous exemplified powertrain technologies is simplified.

A minimal or no cost is projected to the user due to implementation of the application in a mobile communications device and the use of existing signal information, i.e. GPS data. Selected powertrain variants are objectively ranked from a fuel and/or energy use perspective to facilitate the comparison and choice for the user.

These and further advantages of the system will be described below with reference to the appended drawing figures.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following text, the invention will be described in detail with reference to the attached drawings. These schematic drawings are used for illustration only and do not in any way limit the scope of the invention. In the drawings:

Figures 1 A-D show alternative powertrains to which the invention is applicable; Figure 2 shows a schematic view of a system according to the invention; Figure 3 shows a schematic vehicle for which energy usage can be estimated; Figure 4 shows a flow chart illustrating the method steps performed according to the invention;

Figure 5 shows a schematic example of data to be displayed to a user;

Figure 6 shows the invention applied on a computer arrangement. DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION

Figures 1 A-1 D show a number of schematic examples of alternative powertrains to which the invention is applicable. Figure 1 A shows a schematically indicated vehicle 101 comprising a conventional powertrain 102 provided with an internal combustion engine (ICE) 103 connected to a driveline. The driveline comprises a transmission 104, such as an automated manual transmission (AMT), for transmitting torque to a vehicle driveline 105. A conventional powertrain of this type can be fuelled by a suitable fossil fuel (petrol, diesel, LNG, CNG, etc.) or biofuel (ethanol, biodiesel, biogas, RME etc.).

Figure 1 B shows a schematically indicated vehicle 1 1 1 comprising a hybrid electric powertrain 1 12 provided with an internal combustion engine (ICE) 1 13 connected to a transmission 1 14, such as an automated manual transmission (AMT), for transmitting torque to a vehicle driveline 1 15. The powertrain is further provided with an electric motor 1 16 connected to the transmission 1 14 and powered by a rechargeable battery 1 17. A hybrid electric powertrain of this type can be fuelled by a suitable fossil fuel (petrol, diesel, LNG, CNG, etc.) or biofuel (ethanol, RME, etc.), or be powered by the electric motor 1 16. The engine 1 13 and the electric motor 1 16 can be used individually or in combination. The battery 1 17 can be charged using the engine 1 13 via the electric motor 1 16, or by regeneration, when braking or travelling down a gradient.

An alternative not described in connection with the above figures is a micro hybrid powertrain. In a micro hybrid powertrain fuel consumption is reduced by avoiding engine idling, for instance by start-stop operation. As the vehicle comes to a stop the engine is switched off, and is immediately started after an indication from the driver to resume operation. No energy regeneration is possible in such powertrains.

Figure 1 C shows a schematically indicated vehicle 121 comprising a plug-in electric powertrain 122 provided with an electric motor 126 connected to a transmission 124 for transmitting torque to a vehicle driveline 125. The electric motor 126 is powered by a rechargeable battery 127. The powertrain is further provided with an internal combustion engine (ICE) 123 connected to the transmission 124. The engine 123 is provided to drive the electric motor 126 as a generator and can be fuelled by a suitable fossil fuel (petrol, diesel, LNG, CNG, etc.) or biofuel (ethanol, RME, etc.). The battery 127 can be charged either from the electric grid (not shown) or by using the engine 123 via the electric motor 1 16, or by regeneration, when braking or travelling down a gradient.

Figure 1 D shows a schematically indicated vehicle 131 comprising a full electric powertrain 132 provided with an electric motor 136 connected to a transmission 134 for transmitting torque to a vehicle driveline 135. The electric motor 136 is powered by a rechargeable battery 137. In a full electric powertrain, all propulsion energy is drawn from the battery 137 that is charged from the electric grid while the vehicle is standing still. Energy consumption is reduced by brake energy regeneration. Figure 2 shows a system 200 according to the invention, which system is arranged to estimating energy usage of alternative powertrains available to a predetermined first vehicle. The system comprises a mobile communications device 201 , such as a smartphone, arranged to exchange data with a remote server 202. The mobile communications 201 can be a mobile phone, a tablet computer, or a similar portable mobile communications device able to download an application, or "app", from the internet, a cloud based service, or similar. The inventive app allows the user to select at least two alternative powertrains that can be supplied with the vehicle to be tested. According to a further example, the user can also select a vehicle model to be tested, prior to selecting a powertrain for the selected vehicle. The app used for the evaluation is started at a suitable first location by a user intending to estimate energy usage using the system. The mobile communications device 201 can travel a route with a vehicle 204. The vehicle 204 does not necessarily have to be the same type as the predetermined or selected vehicle with alternative powertrains to be tested.

The mobile communications device 201 is arranged to receive position data and time, i.e. a time stamp for the actual position, from satellites 203 (one shown) forming part of the Global Positioning System, commonly termed GPS, during operation of the vehicle. The GPS provides location (position coordinates), and time information for that location in all weather conditions, anywhere on or near the earth where there is an unobstructed line of sight to four or more GPS satellites. In addition to GPS, other suitable systems include the Russian Global Navigation Satellite System (GLONASS), the Indian Regional Navigation Satellite System, and the Chinese Bei Dou Navigation Satellite System, as well as the planned European Union Galileo positioning system. The mobile communications device 201 is located in a suitable position in a vehicle 204, preferably in an area that ensures good GPS reception. The mobile communications device 201 receives GPS data 21 1 from multiple satellites 203 at a predetermined capture rate and transmits data 212 comprising multiple sets of at least position data and time to the remote server 202 via a wireless network 205.

The remote server 202 is arranged to determine a road profile and a speed profile for a route travelled by the vehicle 204, based on the received data 212 and altitude related data. The road profile describes variations in altitude along the route travelled by the vehicle 204, while the speed profile describes variations in vehicle speed, including accelerations and decelerations, along this route. The altitude related data can be determined in a number of different ways from available data or signals. The mobile communications device can be arranged to calculate an altitude for each position using the GPS data and transmit altitude related data to the remote server. Alternatively, or in addition, the mobile communications device is arranged to calculate an altitude for each position using a signal from an internal pressure sensor that can detect changes in atmospheric pressure, or from an accelerometer that can detect positional changes of the device. The remote server can also retrieve altitude related data for each position from a database. These arrangements for determining altitude related data can be used singly or be used in any suitable combination for improved accuracy. The remote server is provided with a speed observer o estimate speed v as function of measured position. Acceleration a is implicitly derived from the observer by numerically calculating the time derivate of the estimated speed. Speed is coupled to position and acceleration as generally expressed in; pbs = v (1) v = a (2) This can be reformulated by; x = [pos v]' = [* _! x ₂ ]' (3) x + G u = [ ₀ ² ] + 0 (4)

%2

Kalman filtering, also known as linear quadratic estimation, is an algorithm that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone. The Kalman filter operates recursively on streams of noisy input data to produce a statistically optimal estimate of the underlying system state. The algorithm works in a two-step process. In the prediction step, the Kalman filter produces estimates of the current state variables, along with their uncertainties. Once the outcome of the next measurement (necessarily corrupted with some amount of error, including random noise) is observed, these estimates are updated using a weighted average, with more weight being given to estimates with higher certainty. Because of the algorithm's recursive nature, it runs in real time using only the present input measurements and the previously calculated state and its uncertainty matrix; no additional past information is required. In the current example, a Kalman filter is utilized to estimate the system states, where observation of internal states is expressed by: ■¾ = <k · ¾ + G _k - u _kA + K _k - (z _k - H - <f> _k - H - G ^■ ¾., )

(5)

In the above equation:

K is the Kalman gain;

H is the observation model;

Q is the covariance of the process noise;

Fk is the state transition model which is applied to the previous state xk-1 ;

G, is a matrix expressing the control input effect on state variables;

0(t) is the fundamental matrix. The remote server is arranged to determine a speed profile for a route travelled by the vehicle 204, based on the received data. The speed profile describes variations in vehicle speed, including accelerations and decelerations, along this route.

The remote server is provided with a slope observer to estimate road slope β as function of measured speed and altitude related data. Altitude z is coupled to speed v and road slope β as expressed in; ζ = ν β (6) β = 0 (7)

This can be reformulated by;

_X = [ _Ζ β]' = [ _Xl x ₂ ] (8) x = + G - u= 7 ² ] ₊ 0 (9)

An extended Kalman filter which works better on nonlinear systems is utilized to estimate the state β.

The remote server is arranged to determine a road profile for a route travelled by the vehicle 204, based on the received data and altitude related data. In this context, the road profile describes variations in altitude along the route travelled by the vehicle.

The remote server 202 is arranged to estimate energy usage data for each of a number of predetermined alternative powertrains selected by the user for the route travelled by the vehicle in real time, based on the determined road and speed profiles. A mathematical model of each powertrain can be used for these calculations. Preferably, one model is provided for every alternative powertrain variant analysed and modelled. As indicated above, the estimation is performed for alternative powertrains available to a predetermined vehicle. For instance, a particular vehicle can be provided with one of a number of alternative powertrains during assembly. Non-limiting examples of alternative powertrains are conventional, micro hybrid, hybrid, plugin-in hybrid, and full electric powertrains.

The app used for the evaluation is stopped at a suitable second location by a user controlling the mobile communications device 201 . Upon receipt of a stop command the remote server 202 is arranged to estimate propulsion power as a function of road slope, speed and acceleration using the determined road and speed profiles and acceleration,. Energy usage data such as fuel and/or electrical energy consumption is calculated by combining propulsion power with a mathematical model of each powertrain. Additional calculations can be performed to determine additional data, such as C0 ₂ and NO _x emission for each powertrain. One model is provided for every powertrain variant to be analysed. The remote server 202 is arranged to estimate energy usage data simultaneously for at least two predetermined alternative powertrains selected by a user. The remote server 202 will then transmit data 213 representing energy usage, C0 ₂ emission and other requested information to the mobile communications device 201 . The mobile communications device 201 is arranged to display estimated energy usage data comprising one or more of fuel consumption, electric energy usage, regenerated energy, and/or emitted C0 ₂ or NO _x . An example of displayed data is shown in Figure 5. The displayed data can vary depending on desired parameters selected for display by the user and/or the types of powertrain selected. In this way, the invention can be used for assisting a user in selecting a powertrain that best suits the user's requirements before purchasing, leasing, or renting a vehicle. The displayed energy usage data provides a simple and educational way of demonstrating which alternative is the most fuel efficient or has the least environmental impact.

Figure 3 shows a schematic vehicle for which energy usage can be estimated. This chapter presents how propulsion power is calculated. Propulsion power is a function of road slope, speed and acceleration, or mathematically:

Pprop Pprop i ^> ^ ¹ >

When calculating propulsion power it is also possible to take into account factors such as rolling resistance and air resistance. These factors can be included depending on the desired accuracy required. For instance, if the vehicle 204 is likely to travel at relatively high speed, then air resistance should be considered. The terms and equations used for this purpose are outlined in Table 1 and the equations listed below.

Table 1.

¹ prop m - a + m - g ^■ sin(a) + / ^■ m ^■ g ^■ cos(a) +— ^■ p _air ^■ CdA ^■ v ²

T ¹ prop Fprop ^{' r} w

¹ p prop Fprop ^' V

Using the determined road and speed profiles and acceleration, determined as described above, propulsion power can be estimated as a function of road slope, speed and acceleration along the route travelled using conventional methods. Energy usage data such as fuel and/or electrical energy consumption is calculated by combining propulsion power with a mathematical model of each powertrain. There is one model for determining energy and fuel consumption for every powertrain variant to be analysed.

For a vehicle with a conventional powertrain the fuel consumption, and thereby the energy consumption is estimated using the above method and the model stored in the remote server. The C0 ₂ , NO _x and particle emissions are proportional to the fuel consumption and is calculated using known methods.

For a vehicle with a micro hybrid powertrain the fuel and energy consumption is calculated in the same way as for the conventional powertrain. In this case the energy consumption will be lower, as a micro hybrid reduces fuel consumption by avoiding engine idling. For a vehicle with a hybrid powertrain the model used for the calculation must consider both fuel consumption and electric power used. In addition, energy can be regenerated at braking. Battery power is calculated in the same manner as for an electric powertrain. The available electric drive power is probably smaller for the hybrid powertrain, compared to an electric powertrain. The stored model will provide a weighted estimate for fuel and electric energy consumption, respectively.

In a vehicle comprising a plugin-in hybrid powertrain the fuel consumption is reduced by brake energy regeneration and by battery charging from the grid while the vehicle is standing still. Optionally, a relative small capacity combustion engine can be used for driving a generator to charge the battery when the vehicle is moving. The vehicle will be mainly powered by the battery, which is taken into account in the stored model for this powertrain when estimating the electric energy consumption, which can be reduced by brake energy regeneration. The model can also take fuel consumption into consideration if applicable. For a vehicle with an electric powertrain the energy consumption minus brake energy regeneration is estimated using the above method and a corresponding model stored in the remote server.

The sign convention is that positive electric machine power corresponds to motor operation, a negative to regeneration. A positive battery power means battery charging. Therefore, the battery power is negative when the electric machine power is positive and vice versa. The parameter η _Γβ3βη reflects the energy regeneration efficiency, typically traction torque must be distributed between driving axles. The consequence is reduced brake energy regeneration efficiency.

An integration of fuel and energy consumption for all powertrains is performed to determine the total energy consumption. This integration can be performed continuously, in real-time as the vehicle travels, or be initiated once a stop command is issued by the user.

Figure 4 shows a flow chart illustrating the method steps performed according to the invention. In order to perform the method the user is required to download an application (app) to a smartphone, a tablet or a similar suitable portable device. When started, the app requires the user to select at least two alternative powertrains to be compared for the predetermined vehicle to be tested. A more advanced version of the app can allow the user to select the desired output data to be displayed and/or to select one of a number of vehicle types or models to be tested. Once the necessary selections have been made, and the user has entered a vehicle (204) to travel the route, the system is ready to start a comparison. When performed on the system shown in Figure 2, the method involves the following steps.

In a first step 401 the user commands the app to "Start evaluation". In a second step 402, the mobile communications device begins reading GPS position signal at a predetermined capture rate. The received signal contains position and a time stamp for that position, which implicitly gives vehicle (204) position and altitude. This data is either processed in the mobile communications device or is transmitted to a remote server for processing. In a third step 403 a vehicle motion state is estimated. The GPS data is used for calculating the vehicle (204) speed along the route travelled by the vehicle 204. The resulting speed profile can be used for calculating accelerations and decelerations, using the time derivative of the speed. Altitude related data can be determined in a number of different ways from available data or signals. Examples of suitable signals are on or more of GPS data from the GPS system, pressure sensor or accelerometer data from the mobile communications device, or stored altitude data from a database containing route information. This data allows a road profile comprising road slope for each position to be determined, wherein road slope is determined as a function of calculated speed and altitude data. In a fourth step 404 a propulsion power calculation is performed where the propulsion power as a function of road slope, speed and acceleration for each position along the route. In a fifth step 405 a calculation of present fuel and energy consumption is performed for the internal combustion engines and electrical motors respectively. In a sixth step 406 an integration of fuel and energy consumption for all powertrains is performed. This integration can be performed continuously, or be initiated once a stop command is issued by the user. In a seventh step 407 the process checks if the user has commanded the app to "Stop evaluation". If no stop command has been issued then the process returns 408 to the second step 402 and continues to read GPS position signals. If a stop command has been issued then the process continues to the next and final step.

In an eight step 409 the process stops and the integrated fuel and energy consumption data is transmitted to the mobile communications device, where the results are presented to the user. Figure 5 shows an example of data to be displayed to a user. According to the example shown in Figure 5, the data can be displayed in a table. An upper portion of the table comprises a first and a second column containing a number of terms and a description thereof. In this case the table displays the travelled Route length (Lroute) measured in kilometres (km), the Maximum speed over the travelled distance (vmax) measured in kilometres per hour (km/h), and the Maximum grade (amax) measured in percent (%). In this example the vehicle has travelled a distance of 10 km, reaching a maximum speed of 60 km/h and the maximum grade over the distance was 6 %.

A lower portion of the table comprises a first and a second column containing terms denoting calculated data for the respective powertrains and a description thereof. In this case the table displays the following data: 1 ) Fuel consumption (Consf _ue i) measured in litres per kilometre (lit/km) for conventional and hybrid powertrains;

2) Diesel energy (E _dieS ei) measured in (kWh/km), converted from fuel consumption;

3) Electric energy (E _e i _ec ) measured in (kWh/km) for hybrid and electric powertrains;

4) Total energy (E _di esei+E _e iec) measured in (kWh/km) for hybrid powertrains;

5) Regenerated energy (Er _ege n) measured in (kWh/km) for hybrid and electric powertrains;

6) Emitted C0 ₂ (Emitt _C o2) measured in (kg/km) for conventional and hybrid powertrains.

From the resulting table the user can quickly establish that a conventional powertrain, in this case diesel powered, has an energy usage of 5 kWh/km with a C0 ₂ emission of 13 kg/km for the route travelled. This can be compared with, for instance, a hybrid-electric powertrain having an energy usage of 4 kWh/km (4 kWh/km of diesel and 0 kWh/km electric) with a C0 ₂ emission of 10 kg/km for the same route. If desired it is also possible to display other emission data, such as NO _x or particles. In this way the user can determine which alternative is the most advantageous from an environmental and/or economical standpoint. The present invention also relates to a computer program, computer program product and a storage medium for a computer all to be used with a computer for executing the method as described in any one of the above examples.

Figure 6 shows an apparatus 600 according to one embodiment of the invention, comprising a non-volatile memory 620, a processor 610 and a read and write memory 660. The memory 620 has a first memory part 630, in which a computer program for controlling the apparatus 600 is stored. The computer program in the memory part 630 for controlling the apparatus 600 can be an operating system.

The apparatus 600 can be enclosed in, for example, a control unit, such as the mobile communications device 201 or the remote server 202. The data-processing unit 610 can comprise, for example, a microcomputer.

The memory 620 also has a second memory part 640, in which a program for the app according to the invention is stored. In an alternative embodiment, the program for the app is stored in a separate non-volatile storage medium 650 for data, such as, for example, a CD or an exchangeable semiconductor memory. The program can be stored in an executable form or in a compressed state.

When it is stated below that the data-processing unit 610 runs a specific function, it should be clear that the data-processing unit 610 is running a specific part of the program stored in the memory 640 or a specific part of the program stored in the non-volatile storage medium 650. The data-processing unit 610 is tailored for communication with the storage memory 650 through a data bus 614. The data-processing unit 610 is also tailored for communication with the memory 620 through a data bus 612. In addition, the data-processing unit 610 is tailored for communication with the memory 660 through a data bus 61 1 . The data-processing unit 610 is also tailored for communication with a data port 690 by the use of a data bus 615.

The method according to the present invention can be executed by the data-processing unit 610, by the data-processing unit 610 running the program stored in the memory 640 or the program stored in the non-volatile storage medium 650.

The invention should not be deemed to be limited to the embodiments described above, but rather a number of further variants and modifications are conceivable within the scope of the following patent claims.