NOISE CANCELLATION SYSTEM FOR A VEHICLE

Abstract

A noise cancellation system for a vehicle, with a microphone for receiving noise and generating a corresponding noise signal; a loudspeaker for emitting an acoustic wave according to a cancellation signal to cancel the noise; a control unit comprising a memory and a controller; wherein the memory has a noise filter; and wherein the controller is configured to obtain at least a vehicle related information of the vehicle; to configure the noise filter based on the at least one vehicle related information; and to generate a cancellation signal based on the noise signal and the noise filter.

Claims

1. A noise cancellation system for a vehicle, the system comprising: a microphone for receiving noise and generating a corresponding noise signal; a loudspeaker for emitting an acoustic wave according to a cancellation signal to cancel the noise; a control unit comprising a memory and a controller, the memory including a noise filter, the controller being configured to— obtain vehicle-related information of the vehicle, configure the noise filter based on the at vehicle-related information, and generate a cancellation signal based on the noise signal and the noise filter.

2. The noise cancellation system of claim 1, wherein the memory includes a modular noise filter including at least two filter parts, a different filter part being adapted to cancel a different noise, and the controller is configured to select at least one of the at least two filter parts to configure the noise filter.

3. The noise cancellation system of claim 1, wherein the vehicle-related information comprises a type of an implement connected with the vehicle.

4. The noise cancellation system of claim 1, further comprising a sensor for detecting a vehicle parameter, the vehicle-related information including the vehicle parameter.

5. The noise cancellation system of claim 1, further comprising a position determination unit for determining a vehicle position, the vehicle-related information including the vehicle position.

6. The noise cancellation system of claim 5, wherein the vehicle-related information includes weather information based on the vehicle position.

7. The noise cancellation system of claim 5, wherein the vehicle-related information includes at least a field property of an agricultural field based on the vehicle position.

8. The noise cancellation system of claim 7, wherein the field property of the agricultural field includes at least a characteristic of plants planted in the agricultural field.

9. The noise cancellation system of claim 5, wherein the controller is configured to determine whether the vehicle is located within an agricultural field based on the vehicle position, and wherein the noise filter is activated if the vehicle is located within the agricultural field.

10. The noise cancellation system of claim 5, wherein the controller is configured to determine whether the vehicle is located outside of an agricultural field based on the vehicle position, and wherein the noise filter is deactivated if the vehicle is located outside of the agricultural field.

11. The noise cancellation system of claim 1, wherein the controller is configured to obtain second vehicle-related information of a second vehicle, wherein the vehicle-related information includes at least the second vehicle-related information of the second vehicle.

12. The noise cancellation system of claim 11, wherein the second vehicle-related information of the second vehicle includes a position of the second vehicle; and wherein the controller is configured to calculate a distance between the both vehicles and to configure the noise filter based on the distance.

13. The noise cancellation system of claim 5, wherein the controller is configured to analyze a teach-in sequence comprising at least a command to be executed automatically by the vehicle at the vehicle position; and to obtain the at least one vehicle related information of the vehicle based on the teach-in sequence.

14. The noise cancellation system of claim 1, wherein the controller is configured to reconfigure the noise filter based on the vehicle-related information if the vehicle-related information of the vehicle has been changed.

15. The noise cancellation system of claim 1, wherein the controller is configured to detect noise exceeding a threshold while a noise filter based noise cancellation is active, and to perform a method for active noise cancellation to cancel the noise exceeding the threshold.

16. The noise cancellation system of claim 15, wherein the controller is configured to generate a new filter part to cancel the noise exceeding the threshold, and to store the new filter part to the memory.

17. The noise cancellation system of claim 1, wherein the controller is configured to analyze the noise, to detect a noise resulting from a damage or a fault of the vehicle, and to exclude the noise resulting from the damage or the fault from noise cancellation.

18. A method for performing noise cancellation, comprising: receiving a noise; generating a noise signal corresponding to the received noise; obtaining at least a vehicle related information of the vehicle; configuring a noise filter based on the at least one vehicle related information; generating a cancellation signal based on the noise signal and the noise filter; and emitting an acoustic wave according to the cancellation signal to cancel the noise.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Several aspects of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0041] FIG. 1 shows an agricultural vehicle comprising a noise cancellation system;

[0042] FIG. 2 shows a control unit for supporting the noise cancellation;

[0043] FIG. 3 shows a flow diagram of a method for performing noise cancellation; and

[0044] FIG. 4 shows an agricultural field and agricultural vehicles operating in the field.

DETAILED DESCRIPTION

[0045] FIG. 1 shows a vehicle 1, e. g. an agricultural machine 1 as a tractor, which comprises a cabin 2 and a noise cancellation system 21. The noise cancellation system 21 comprises a loudspeaker 3 and a microphone 4 that are both installed in the cab 2 and a control unit 5 installed in the vehicle 1. A global navigation satellite system (GNSS) receiver 6 is mounted on the roof of the cabin 2. The GNSS receiver 6 receives signals from a GNSS 7, in particular position signals for determining the position of the vehicle 1.

[0046] As shown in FIG. 4, the vehicle 1 may be connected to a first, front implement 10, for example a front mower, and a second, rear implement 11, for example a loader wagon. A drone 19 may determine field data about geodetic data and 3D mapping data about vegetation and plant coverage of an agricultural field 14 and transmit all data to the control unit 5 of the vehicle 1.

[0047] Optionally, the loudspeaker 4 can be integrated in a portable device with or without an additional external microphone, such as a headset, headphones, hearing aid, etc. The portable device is connectable to the control unit 5, e. g. via Bluetooth® or other wireless signal transfer method or also wired transfer.

[0048] FIG. 2 shows the control unit 5 comprising a controller 8 and a memory 9. The memory 9 contains data and executable programs (computer-implemented procedures or methods) that can be retrieved, processed and executed by the controller 8. The controller 8 can also store data in the memory 9. The controller 5 is connected to all devices of the agricultural machine 1 as the microphone 3, the speaker 4, the GNSS receiver 6 and a sensor 20.

[0049] FIG. 3 shows a flow diagram of a method stored as a computer-implemented method in the memory 9. The method is executed by the noise cancellation system 21 and can be started automatically (S100), e. g. when an engine of the agricultural machine 1 is started. Then, in step S101, active noise cancellation (ANC) is activated in order to eliminate disturbing sound waves propagating in the cabin 2.

[0050] The disturbing sound waves can be, for example, driving noises (engine noises, rolling noises of the tires, driving wind noises, noises of an implement, etc.) which occur while the vehicle 1 is stationary or driving along a road 13, field path or field 14 under the most varied combination and load scenarios.

[0051] The disturbing sound waves are sensed by the microphone 3 and converted into signals. The signals are fed to the control unit 5. Thereupon the controller 8 evaluates the signals and generates signals for noise cancellation to emit a counter noise with a sound wave path of 180° (=half a wavelength) opposite to the disturbing noise. The counter noise is then output by the loudspeaker 4 in the cabin 2. As a result of the ANC, the sound waves from the disturbing noise and the counter noise overlap and cancel out each other.

[0052] This conventional method of noise elimination works very well for monotonous noises, such as an engine noise or a tire rolling noise. In case of a changing background noise, for example when an agricultural machine is operating in the agricultural field 14, delays in the noise cancellation can be perceptible to the operator of the vehicle 1 although the noise cancellation takes place almost in real time.

[0053] Therefore, according to an aspect of the invention the ANC will be optimized for field work or off-road applications. The controller 8 can obtain at least one vehicle related information of the vehicle 1 to configure the noise filter based on the at least one vehicle related information. The method comprises several steps to determine various vehicle related information (see steps S102 to S108).

[0054] The method continues with step S102 and the controller 8 determines the position of the vehicle 1 based on the GNSS 7 position signals received from the GNSS receiver 6.

[0055] In the following step S103, the controller 8 checks whether the vehicle 1 is located in the agricultural field 14. As long as the vehicle 1 is outside the field 14, the query after step S103 is repeated continuously.

[0056] As shown in FIG. 4, it is assumed now that the vehicle 1 with the front implement 10 and the rear implement 11 drives onto the agricultural field 14 from a road 13 or field path. The position of the vehicle 1 is tracked or monitored by the GNSS 7 and/or the drone 19. The positional information can be sent to the controller 8. Based on the position check, the controller 8 detects that the vehicle 1 is now in the field 14 and activates the off-road mode of the ANC in response.

[0057] With the off-road mode of the ANC activated, the controller 8 configures a noise filter adapted to the configuration of the vehicle 1, to its area of use and to its environment of use and performs noise reduction or noise elimination by means of this noise filter.

[0058] The controller 8 can be configured to select at least a fixed filter part out of several fixed filter parts. All fixed filter parts can be stored in the memory 9. The fixed filter parts can be used as modules to create a modular noise filter. The controller 8 can select two or more filter parts and combine them for the configuration of the (modular) noise filter. The modular noise filer can be stored in the memory 9. Besides the configuration of the noise filter the controller 8 can optionally be configured to optimize an existing fixed filter part and/or to create a new fixed filter part by a self-learned filter part to be stored in the memory 9.

[0059] The configuration of the noise filter can be based on known and/or by at least a sensor detectable environmental conditions when the vehicle 1 is operating to build up and continuously extend a database stored in the memory 9 by the control unit 5. The control unit 5 uses the extended database to generate the best possible performance for the counter noise.

[0060] Fixed Filter Part:

[0061] For the configuration of the fixed filter part, the controller 8 accesses a database stored in the memory 9. The database comprises filters already determined for the corresponding vehicle or implement.

[0062] After the controller 8 has recognized that the vehicle 1 is driving in the field 14, i. e. off the road 13, the method according to FIG. 3 continues with the configuration of the fixed filter part. To do this, at least one of the steps S104 to S108 is carried out. This means that all steps S104 to S108 can be carried out in any order or individual steps can be skipped or omitted.

[0063] The individual steps will be explained now in more detail.

[0064] According to step S104, the configuration of the vehicle 1 is checked. As can be seen from FIG. 4, the vehicle 1 is connected to a first, front implement 10, e. g. a front mower, and a second, rear implement 11, e. g. a loader wagon. This vehicle configuration is only exemplary. In principle, all vehicle combinations are possible. For example, instead of a tractor, another machine such as a forage harvester can be used.

[0065] The controller 8 can recognize which vehicle 1 or combination of machines is used. Corresponding data is stored in the memory 9 or can be retrieved from the implements 10 or 11 by the controller 8 for example via a data link as ISOBUS. Alternatively, the user of the vehicle 1 can be prompted to specify the corresponding configuration of the vehicle 1, e. g. by means of a configuration menu, for providing the data to the controller 8.

[0066] Based on the detected configuration of the vehicle 1, the controller 8 evaluates all parameters which are related to the configuration of the vehicle 1 and are relevant for the configuration of the filter. The parameters can depend on among others:

[0067] Type of cab, type of engine, type of transmission, equipment line, equipment options, type of pneumatic system, driving conditions, wheel speed, vehicle speed, slip, tire pressure, type of tire tread, tread depth, tire size, tire age, number of tires, wheel weight, vehicle weight, load, type of front loader, engine speed, transmission speed, all-wheel drive, activation of differential, activation of brake, steering angle, activation of cruise control, PTO speed, interior noise, type of suspension, activation of air conditioning, position of windows, roof hatch or door (opened or closed), activation of windscreen wipers, mirror adjustment, activation of hydraulic system (valves, hydraulic pump (speed, flow rate)), etc.

[0068] Based on the recognized or selected (ISOBUS) implement, the parameters can depend on among others: PTO input speed, type of sub-gearbox, activation of conveyor belt, load, speeds, type of pumps, type of motors, etc.

[0069] Depending on the configuration of the vehicle 1 and how its signals or parameters vary, the noise generated by the vehicle 1 will vary.

[0070] For example, the vehicle 1 will produce a recurring noise when accelerating from a first engine speed, e. g. 1500 rpm, to a second engine speed, e. g. 1900 rpm. However, this noise will vary depending on the gear selected for the transmission. I. e., acceleration with a selected first gear will produce a different noise than acceleration with a selected second or a selected third gear even when accelerating from the same first to the same second engine speed for all selected gears. The other parameters may behave similarly.

[0071] Since the controller 8 is aware of the configuration of the vehicle 1 and permanently monitors the operating conditions, the controller 8 can react immediately and practically without delay to the prevailing noise generation. The controller 8 selects the filter settings required for noise cancellation according to the detected configuration of the vehicle 1 and the parameters for the fixed filter part from the database stored in memory 9. The controller 8 adjusts the noise filter immediately in the event of a change of the configuration of the vehicle 1 or a change of the parameters.

[0072] Thus, an advantage over conventional ANC can be achieved: The disturbing frequencies of the noises are known (stored in the memory 9) and are expected by the controller 8 based on the detected configuration and parameterization of the vehicle 1. Therefore, the noises can be detected more quickly and subsequently filtered better. The time delay from the detection by the controller 8 to the output of the counter sound for noise cancellation by the loudspeaker 4 is minimized compared to a constant ANC readjustment.

[0073] The method proceeds to step S105. According to step S105, the field characteristics are checked at the position where the vehicle 1 is located in the field 14 and can be determined as vehicle related information of the vehicle 1. The control unit 5 may request the position of the vehicle 1 from the GNSS receiver 6. Alternatively or additionally, the control unit 5 can determine the positions of the vehicle 1 in the field 14 in advance on the basis of paths 16 selected by the user, e. g. from an existing database.

[0074] The relevant data and parameters regarding areas of the field 14, such as stored paths 16, headland 15, special ground conditions as wet spots 18, obstacles 17 within the field 14 or other vehicles 12 operating in the field 14 are determined and taken into account accordingly by the controller 8 for the configuration of the noise filter.

[0075] The controller 8 compares the position of the vehicle 1 with a map of the field comprising field properties stored in the memory 9 and determines the corresponding field properties present at the position of the vehicle 1 in the field 14. Depending on the field properties, different noises can be expected. For example, the field 14 may comprise potholes 17 and/or damp or wet spots (puddles) 18. When the vehicle 1 drives over these field areas 17, 18 different disturbing noises due to changing conditions will occur which in turn differ from the noises when driving over the field 14 outside these field areas 17 or 18.

[0076] The following additional field properties can influence the occurrence of the disturbing noises: Topography, gradients (driving uphill, downhill), furrows, arable land, meadow, different soil or subsoil conditions (potholes, loamy, stony, rocky subsoil, wet spot, soil moisture), vegetation, etc.

[0077] If the controller 8 is aware of the current conditions about seed, type of plants, moisture of plants, height of vegetation, etc. in the field (e. g. by evaluating a map of the field comprising all this data) this data can be considered for the configuration of the noise filter and the selection of a corresponding filter part.

[0078] The paths 16 and the tasks of prior field operations executed along the paths 16 (e. g. seeding of specific seeds) can be stored in the database. Thus, the controller 8 can recognize, for example, the type of crop to be harvested at a later field operation based on the information of the database. Since harvesting of corn produces different sounds than harvesting of grain, the fixed filter part can be configured according to the specific crop to be harvested.

[0079] The database can also comprise geodetic data including additional 3D mapping data of vegetation and growth of plants (crop) captured by a drone 19.

[0080] Based on the determination of the field properties present at the position of the vehicle 1 the expected noises can be determined in advance by the controller 8 and the filter parts required for noise cancellation can be selected for the configuration of the noise filter.

[0081] According to step S106, a teach-in sequence to be executed by the vehicle 1 is analyzed by the controller 8 with regard to the disturbing noises to be expected. Since the tasks of the vehicle 1 and its implements 10 and 11 for the field operation are predetermined by the teach-in sequence, the expected noises occurring during the field operation can be determined in advance by the controller 8. Consequently, the controller 8 can pre-configure the fixed noise filter accordingly by selecting an appropriate filter part for each task.

[0082] According to step S107, the weather data and data derived thereof can be determined by the controller 8 as additional vehicle related information of the vehicle 1 based on the position of the vehicle 1

[0083] The controller 8 can receive professionally prepared weather data from various online archives. The weather data can be based on detailed topography (up to 90 meters accuracy) comprising precise values of latitude and longitude. The weather data can additionally be used for determining the current wind speed, the ground temperatures (in 5 to 10-minute intervals) and precipitation amounts in the last (e. g. 48) hours, etc. as well as the current weather situation for the selection of appropriate filter parts in this regional area and the configuration of the noise filter.

[0084] According to step S108, the controller 8 determines the presence of further vehicles 12 operating in the field 14 near to the vehicle 1 as additional vehicle related information of the vehicle 1. For example, the controller 8 can receive the position and the type of the further vehicle 12, as well as information about the field operation executed by the vehicle 12. Based on this information, the controller 8 selects an appropriate filter part and configures the noise filter. Thus, noise of the further vehicle 12 intruding into the cab 2 of the vehicle 1 can be cancelled.

[0085] After steps S102 to S108 have been run through, the controller 8 has determined vehicle related information of the vehicle 1 in order to select the filter parts needed and to configure the noise filter accordingly in the following step S109. In step S109, the vehicle related information is processed by the controller 8. The controller 8 configures the noise filter by combining the selected filter parts so that the settings required to cancel the expected noises are made by the corresponding filter parts in accordance with steps S102 to S108.

[0086] Then, the controller 8 continues with step S110 and analyses the noise recorded by the microphone 3. If noise is detected that potentially indicates damage or a fault of the vehicle 1 this noise is excluded from the filtering or processed separately. If the controller 8 detects an impending damage or fault, it issues a warning to the user of the vehicle 1.

[0087] The method of FIG. 3 continues with step S111 and checks whether the ANC should be switched off in order to carry out noise elimination using the noise filter only, or whether the ANC should remain active in order to optimize the noise filter using a self-learned filter part. The decision whether to switch off the ANC can be made by the user of the vehicle 1 or automatically decided by the controller 8.

[0088] If the controller 8 detects an inhomogeneity, latency or indifference exceeding a predefined threshold for the noise cancellation the user of the vehicle 1 will be informed by a message (warning signal, pop-up, etc.) that the self-learning mode can be started manually.

[0089] Alternatively, the controller 8 can automatically detect at step S111 that an optimization of the noise filter is required. Then, the procedure for optimizing the noise filter is started automatically by the controller 8 at step S113 to determine the data set of a self-learned filter part.

[0090] If no optimization of the noise filter shall be performed by a self-learning procedure the method continues with step S112 and the controller 8 deactivates the ANC.

[0091] Then, the method proceeds to step S115 and the controller 8 generates a signal for a counter-sound based on the fully configured noise filter and sends this signal to the loudspeaker 4 for emitting the counter-sound and cancelling the disturbing noise.

[0092] If an optimization of the noise filter shall be performed by a self-learning procedure the method continues with step S113. The controller 8 uses the existing filter parts as well as the data of the operating states of the vehicle 1 and the implements 10, 11 stored in the memory 9 as a basis for a self-learning process of further filter parts.

[0093] The controller 8 analyzes the existing filter parts in more detail by processing the received noise from the microphone 3 using the ANC. The analyzed filters are stored in the memory 9 when they reach a certain amount of data. Thus, a more detailed data basis of all existing operating states with various combinations of implements 10 or 11 in each driven field area is created by the ANC using an online location and position determination under consideration of the weather data (cf. step S107), movement states, etc. If the quality and effectiveness of the filtering is within the range of the predefined thresholds the data is stored to the memory 9 and serves as a basis for the filter parts to be selected.

[0094] The quality and effectiveness of the filtering is actively monitored at all times. If any inhomogeneity, latency or indifference of the filtered noises is detected, e. g. caused by new background noise, a modified filtering (see S113) and a further noise cancellation are initiated. The implementation of artificial intelligence (AI) can support a more sensitive and efficient self-learning procedure. Then, the data is saved and used as a basis (see S115) for any later filter selection.

[0095] The new self-learned filter part is added to the memory 9 and made available as an additional filter part that can be selected by the controller 8.

[0096] The method continues with step S114 and the controller 8 performs an ANC to minimize the noise that cannot be filtered out by the at least one fixed filter part or for which no suitable filter part is yet available in the database.

[0097] Then, the method proceeds to step S115 and the controller 8 generates a signal for a counter-sound based on the fully configured noise filter and sends this signal to the loudspeaker 4 for emitting the counter-sound and cancelling the disturbing noise.

[0098] The method ends then with the following step S116.