Description:TECHNICAL FIELD
[0001] The present invention relates to methods and systems for detecting the type of terrain to provide driver assistance. Such driver assistance may constitute a part of any automobile, a motorcycle, a scooter, and other road-traveling automobiles.
BACKGROUND
[0002] Increasingly, vehicles are being equipped with sensors that generate data describing the surrounding environment and terrain. For example, some vehicles include camera systems that provide images of the terrain and/or other objects in the vicinity of the vehicle. Further, automotive active safety sensors such as radars have been used to detect the presence, reflectance intensity, and positions of objects in the vehicle's path. The data generated by these sensors may be utilized by various vehicular systems to provide vehicle control, collision avoidance, adaptive cruise control, collision mitigation and other active safety features.
[0003] However, the performance of many sensors is adversely affected by certain road, weather, and other environmental conditions. For example, the performance of a vehicular camera system can be significantly degraded by conditions that affect outside visibility, such as sudden lighting changes (e.g., tunnel transitions) or inclement weather (e.g., fog, rain, snow, etc.). In addition, the performance of automotive radars can be degraded by road debris, inclement weather, and other signal interference that result in misclassification of a radar target or inaccurate position determinations.
[0004] One of the conventional techniques for terrain classification include the use of radar cross section (RCS) backscatter for single polarization synthetic aperture radar (SAR) or examining the scattering physics using multiple-polarization SAR. There are a number of issues to be addressed when solely relying on radar backscatter. For a single-polarization radar operating over a fixed range of frequencies, terrain backscatter is strongly dependent on not only the material itself, but also an antenna to terrain geometry during radar imaging. Furthermore, the moisture content of the material, such as soil, may change and, hence, impact the radio frequency (RF) reflectivity. The result is different types of terrain may exhibit similar radar backscatter, thus leading to detection and classification ambiguity. Another approach for performing terrain classification using SAR images requires multi-polarization SAR image systems, which are often unavailable.
[0005] In light of the above-stated discussion, it is desirable to provide a method of detecting the terrain through which the electric vehicle is traveling to implement and/or improve rider assistance. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.

OBJECT OF THE DISCLOSURE
[0006] A primary objective of the present disclosure is to provide a terrain detecting system for detecting a type of terrain for use with an electric vehicle.
[0007] Another objective is to provide a method for detecting a type of terrain an electric vehicle is traveling through.
[0008] Yet another objective is to provide and/or improve rider assistance based on the road surface properties such as gradient of road, coefficient of friction of road, bumps and potholes on road.

SUMMARY
[0009] An embodiment of the present invention relates to a method of detecting a type of terrain surrounding an electric vehicle by a terrain detection electronic control unit (ECU) includes a plurality of terrain sensors, a gradient detection unit, a coefficient of friction unit, a bump and pothole detection unit, and a surface detection unit to perform multiple steps. In the first step, the plurality of terrain sensors receives a terrain data of roads on the electric vehicle. In the next step, the terrain detection unit analyses at least one road surface properties including a gradient of road, a coefficient of friction of road, bumps and potholes on the road based on obtained terrain data. Further, the gradient detection unit is configured to calculate the gradient of road. Further, the coefficient of friction unit is configured to estimate the coefficient of friction of road. The bump and pothole detection unit is configured to detect bumps and potholes on the road. The surface detection unit is configured to detect surface of road. The terrain detection electronic control unit (ECU) is determined the type of terrain based on the at least one road surface properties.
[0010] In accordance with an embodiment of the present invention, the plurality of sensors includes a motor encoder, an Inertial measurement unit (IMU) sensor, a wheel speed sensor and alike. Further, the type of terrain is any one of an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
[0011] In accordance with an embodiment of the present invention, the electric vehicle is any of a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a Plug-in Hybrid electric vehicle (PHEV) Fuel Cell electric vehicle (FCEV), a two-wheeler electric bike, a three wheeler electric vehicle. Further, the user device is configured with an input interface that is anyone of a smartphone, a laptop, a dashboard, or a button placed on the electric vehicle.
[0012] In accordance with an embodiment of the present invention, the gradient of the road is calculated by the gradient detection unit. In particular, the gradient detection unit is configured to determine a state observer, an accelerometer reading, and estimated accelerations. Further, the gradient detection unit is configured to scale and rotate an accelerometer reading and a gyroscope reading from an IMU reference frame to a vehicle reference frame. Further, the gradient detection unit corrects the accelerometer reading by measuring a vehicle speed at a steady state and removing scales. The gradient detection unit determines an euler angle from the gyroscope readings by the state observer and corrects the euler angle by calculating a difference between the accelerometer readings and estimated accelerations to get the gradient. Further, the vehicle speed along with gyroscope readings is used as an input to the state observer.
[0013] In accordance with an embodiment of the present invention, the vehicle speed is calculated by the motor encoder and the wheel speed sensor. Further, a vehicle pitch of the electric vehicle is equal to road gradient.
[0014] In accordance with an embodiment of the present invention, the coefficient of friction of road is estimated using the coefficient of friction unit. In particular, the coefficient of friction unit is configured for measuring a vehicle acceleration and a speed profile of the electric vehicle, applying a motor torque and a brake pressure to the electric vehicle the state observer to model behavior of the electric vehicle over surfaces having different coefficients of friction. Further, the coefficient of friction unit calculates an expected vehicle speed of the electric vehicle based on the behavior of the electric vehicle over surfaces having different coefficients of friction and comparing measured vehicle speed from the motor encoder and wheel speed sensor with the expected vehicle speed to estimate the coefficient of friction.
[0015] In accordance with an embodiment of the present invention, bump and pothole are detected using the bump and pothole detection unit by determining a change of orientation of the electric vehicle along with accelerations of the electric vehicle based on sensor readings from accelerometer, gyroscope, motor encoder and wheel speed sensors, transforming the sensor readings to the vehicle reference frame to obtain longitudinal accelerations and vertical accelerations of the electric vehicle. The bump and pothole detection unit in configured for deriving a vehicle pitch for the electric vehicle based on the state observer, the accelerometer readings, and estimated accelerations, storing a historical data of the vehicle pitch of the electric vehicle on a controller for “N” vehicle pitches. Further, the bump and pothole unit determines the peaks formed by the vehicle pitch data of the electric vehicle at different frequencies depending on vehicle speed using a fast fourier transform and compares the vehicle speed of the electric vehicle with a predicted profile of bumps and potholes to determine whether bumps and potholes are detected on the terrain of the electric vehicle.
[0016] Further, the peak is formed at a low frequency compared to the vehicle speed indicates bump or pothole is detected, and the peak formed at a high frequency compared to the vehicle speed indicates no bump or pothole is detected.
[0017] In accordance with an embodiment of the present invention, a wheel speed sensor data acquired from the wheel speed sensor is compared to the speed profiles of the electric vehicle on bumps and potholes to detect the bump or pothole. The bump and pothole detection unit is further configured to track vehicle suspension health and a rider behavior.
[0018] In accordance with an embodiment of the present invention, the motor torque and the brake pressure determine a total tractive force applied to the electric vehicle. Further, the expected vehicle acceleration and the speed profiles of the electric vehicle is determined with the help of a mass estimate of the electric vehicle
[0019] In accordance with an embodiment of the present invention, the gradient detection unit is operably configured to activate and/or deactivate a hill assisting module.
[0020] Another embodiment relates to a terrain detecting system for use with an electric vehicle to detect a type of a terrain. The system comprising a user device, a virtual platform, a processor, a plurality of terrain sensors, and a communication network. The user device is configured to display the plurality of road surface properties including a gradient of road, a coefficient of friction of road, bumps and potholes on road the electric vehicle is traveling through. Further, the virtual platform including the plurality of databases and a memory to store data. The virtual platform is either of a cloud server or the electric vehicle. Further, the processor is operably configured with a terrain detection electronic control units (ECU) and a plurality of modules to execute one or more instructions preferably stored within the memory. Further, the plurality of terrain sensors is configured to obtain a terrain data of roads to be travelled by the electric vehicle. In particular, the terrain detection electronic control unit is configured to detect the type of terrain. Further, a gradient detection unit to calculate a gradient of road, a coefficient of friction unit to estimate a coefficient of friction of road, a bump and pothole detection unit to detect bumps and potholes on roads, a surface detection unit to detect surface of roads. Further, the communication network is configured to allow communication between the virtual platform, the plurality of databases, the user device, and the terrain detection electronic control units (ECU).
[0021] In accordance with an embodiment of the present invention, the type of terrain is any one of an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
[0022] In accordance with an embodiment of the present invention, the electric vehicle is any of a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a Plug-in Hybrid electric vehicle (PHEV) Fuel Cell electric vehicle (FCEV), a two wheeler electric bike, a three wheeler electric vehicle.
[0023] In accordance with an embodiment of the present invention, the user device is configured with an input interface that is any of a smartphone, a laptop, a dashboard, or a button placed on the electric vehicle, among others.
[0024] These and other aspects herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawing.
[0025] It should be understood, however, that the following descriptions are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the invention herein without departing from the spirit thereof. The foregoing objectives are attained by employing an automatic salt level sensing device and a method of indicating a low salt level thereof.

BRIEF DESCRIPTION OF FIGURE
[0026] Having thus described the disclosure in general terms, reference will now be made to the accompanying figure, wherein
[0027] Fig. 1 is a block diagram illustrating a terrain detecting system for use with a vehicle to detect a type of terrain an electric vehicle in accordance with an embodiment of the invention;
[0028] Fig. 2 is a block diagram illustrating different terrain detection electronic control units (ECU) in accordance with an embodiment of the present invention;
[0029] Fig. 3 is a flowchart illustrating a method to detect a type of terrain travelled by an electric vehicle in accordance with an embodiment of the present invention;
[0030] Fig. 4 is a flowchart illustrating a method to calculate gradient of road in accordance with an embodiment of the present invention;
[0031] Fig. 5 is a flowchart illustrating a method to calculate coefficient of friction in accordance with an embodiment of the present invention;
[0032] Fig. 6 is a flowchart illustrating a method to detect bump and pothole on roads in accordance with an embodiment of the present invention.
[0033] It should be noted that the accompanying figure is intended to present illustrations of a few examples of the present disclosure. The figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale.

DETAILED DESCRIPTION
[0034] In the following detailed description of the invention, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be obvious to a person skilled in the art that the invention may be practiced with or without these specific details. In other instances, well known methods, procedures and components have not been described in detail so as not to unnecessarily obscure aspects of the invention.
[0035] Furthermore, it will be clear that the invention is not limited to these alternatives only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art, without parting from the scope of the invention.
[0036] The accompanying drawing is used to help easily understand various technical features and it should be understood that the alternatives presented herein are not limited by the accompanying drawing. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawing. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0037] It will be apparent to those skilled in the art that other alternatives of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention. While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific aspect, method, and examples herein. The invention should therefore not be limited by the above described alternative, method, and examples, but by all aspects and methods within the scope of the invention. It is intended that the specification and examples be considered as exemplary, with the true scope of the invention being indicated by the claims.
[0038] Conditional language used herein, such as, among others, "can," "may," "might," "may," “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain alternatives include, while other alternatives do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more alternatives or that one or more alternatives necessarily include logic for deciding, with or without other input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular alternative. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list.
[0039] Disjunctive language such as the phrase “at least one of X, Y, Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain alternatives require at least one of X, at least one of Y, or at least one of Z to each be present.
[0040] Terms rider assistance and driver assistance may be used interchangeably for convenience.
[0041] Terms vehicle and electric vehicle may be used interchangeably for convenience.
[0042] Terms electronic control unit or ECU may be used interchangeably for convenience.
[0043] Fig. 1 is a block diagram illustrating a terrain detecting system 100 for use within an electric vehicle 122 to detect the type of terrain and provide better and/or improved driver assistance in accordance with an embodiment of the invention. The terrain detecting system 100 operates in a vehicle environment. The electric vehicle 122 is anyone but not limited to a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a Plug-in Hybrid electric vehicle (PHEV) Fuel Cell electric vehicle (FCEV), a two wheeler electric bike, and a three wheeler electric vehicle. Further, the type of terrain is any one of an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
[0044] The terrain detecting system 100 includes a virtual platform 104 with a plurality of databases 102A-102I (hereinafter cumulatively referred to as database 102), a memory 106 with a plurality of modules 107, a communication network 108, a processor 110, an electronic control units (ECU) 111, a user device 112.In accordance with an embodiment of the present invention, the virtual platform 104 may be configured with the memory 106 to store the plurality of databases 102A-102I that helps in establishing communication with the user device 112, the terrain detecting system 100 and the processor 110 via the communication network 108. Further, the virtual platform (104) is either of a cloud server or the electric vehicle (122). In particular, the cloud server may be, but not limited to a cloud server, a web server, an application server, a proxy server, a network server, or a server farm, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the remote server, including known, related art, and/or later developed technologies.
[0045] In some implementations, the virtual platform 104 communicates with the terrain detecting system 100 via a virtual private network (VPN), Secure Shell (SSH) tunnel, or other secure network connection.
[0046] In accordance with an embodiment of the present invention, the data utilized by the processor 110 may be sent as notifications to the virtual platform 104.
[0047] In accordance with an embodiment of the present invention, the communication network 108 is configured for providing communication links for communicating with the virtual platform 104, the user device 112, memory 106, plurality of modules 107 processor 110, electronic control units (ECU) 111 and the vehicle 122.
[0048] In particular, the communication network 108 may any communication network, such as, but not limited to, the Internet, wireless networks, local area networks, wide area networks, private networks, a cellular communication network, corporate network having one or more wireless access points or a combination thereof connecting any number of mobile clients, fixed clients, and servers and so forth. Examples of communication network 108 may include the Internet, a WIFI connection, a Bluetooth connection, a Zigbee connection, a communication network, a wireless communication network, a 3G communication, network, a 4G communication network, a 5G communication network, a USB connection, or any combination thereof. For example, the communication may be based through a radio-frequency transceiver (not shown). In addition, short-range communication may occur, such as using Bluetooth, Wi-Fi, or other such transceivers.
[0049] It will be appreciated that the network connections shown are illustrative and other means of establishing a communications link between the computers may be used. The existence of any of various network protocols such as TCP/IP, Ethernet, FTP, HTTP and the like, and of various wireless communication technologies such as GSM, CDMA, WiFi, and WiMAX, is presumed, and the various computing devices and system components described herein may be configured to communicate using any of these network protocols or technologies.
[0050] In some implementations, the terrain detection system 100 may be a distributed client/server system that spans one or more communication networks (not shown).
[0051] In accordance with an embodiment of the present invention, the memory 106 is configured to store the plurality of modules 107. The memory 106 is any type of suitable memory, including various types of dynamic random access memory (DRAM) such as SDRAM, various types of static RAM (SRAM), and various types of non-volatile memory (PROM, EPROM, and flash). It should be understood that the memory 106 may be a single type of memory component or it may be composed of many different types of memory components. As noted above, memory 106 stores instructions for executing one or more methods including embodiments of the methods for determining when a task may be performed on the electric vehicle 122 described below. In addition, the memory 106 may be configured to store various other data as further described below.
[0052] For example, the memory 106 may store software used by the user device 112, such as an operating system (not shown), application programs (not shown), and an associated internal database (not shown).
[0053] In accordance with an embodiment of the present invention, the processor 110 is communicably connected to the modules 107 and electronic control unit 111 to perform a series of computer-readable instructions. The processor 110 may be any well-known processor, but not limited to processors from Intel Corporation. Alternatively, in another embodiment, the processor 110 may be a dedicated controller such as an ASIC. Further, the processor 110 may be any of an ARM, MIPS, SPARC, or INTEL® IA-32 microcontroller or the like.
[0054] Similarly, in yet another embodiment of the present invention, the processor 110 comprises a collection of processors which may or may not operate in parallel.
[0055] Alternatively, the processor 110, which may be any processor-driven device, such as may include one or more microprocessors and memories or other computer-readable media operable for storing and executing computer-executable instructions.
[0056] As used herein, the term "computer-readable media" may describe any form of computer memory or memory device, such as, but not limited to, a random access memory ("RAM") or a non-volatile memory, such as a hard disk, memory card, ROM, RAM, DVD, CD-ROM, USB Flash drive, write-capable, and read-only memories an EPROM, or an EEPROM.
[0057] Examples of processor-driven devices may include, but are not limited to, a server computer, a mainframe computer, one or more networked computers, a desktop computer, a personal computer, an application-specific circuit, a microcontroller, a minicomputer, or any other processor-based device.
[0058] The processor 110 may execute any set of instructions directly as computer executable codes or indirectly (such as scripts). In that regard, the terms “instructions,” and “steps” may be used interchangeably herein. The instructions may be stored in object code form for direct processing by the processor, or in any other computer language including scripts or collections of independent source code modules that are interpreted on demand or compiled in advance. The processor may be remotely placed or locally placed on the server.
[0059] The terrain detecting system 100 may also include one or more input/output ("I/O") ports (e.g., serial ports, (e.g., RS233 port, USB, etc.) (not shown) and one or more network interfaces. The I/O port or ports may be operable to communicate with input/output devices, such as an internal and/or external display, keypad, mouse, pointing device, control panel, touch screen display, another computer-based device, printer, remote control, microphone, speaker, etc., which facilitates user interaction with the terrain detecting system 100.
[0060] The terrain detection electronic control units (ECU) 111 includes one or more automotive control units for controlling the various systems of the vehicle 122. In particular, the terrain detection electronic control units (ECU) 111 includes a gradient detection unit 205, a coefficient detection unit 210, a bump and pothole detection unit 215 and a surface detection unit 220. Each terrain detection electronic control unit (ECU) 111 includes one or more controllers, actuators, sensors, and/or other components that control the operation, handling, and other characteristics of the vehicle.
[0061] In accordance with one embodiment of the present invention, a plurality of terrain sensors 114 generates data describing the terrain and other bumps and potholes within at least a portion of the area surrounding the electric vehicle 122. In the embodiments described herein, the bumps and potholes may have a portion of the area in front of the electric vehicle 122. However, it will be appreciated that the bumps and potholes may comprise all or other portions of the area surrounding the electric vehicle 122. In one embodiment, the plurality of terrain sensors 114 may include but not limited to a motor encoder, an Inertial measurement unit (IMU) sensor, a wheel speed sensor and alike.
[0062] In an alternate embodiment, the plurality of terrain sensors 114 may also include the dissimilar terrain sensing devices, such as one or more Light Detection and Ranging devices (hereinafter, “LIDAR(s)”), camera(s), and radar(s). It should be noted that other terrain detecting devices (e.g., ultrasounds) may also be utilized.
[0063] In accordance with one embodiment of the present invention, the electric vehicle 122 may have a camera(s) to generate images of the road, painted road markers (e.g., lane markers), other vehicles, potholes, bumps and other objects within the surrounding areas. The camera(s) may include stereo cameras that generate images depicting the height/elevation and curvature of the surface of the target area. Radar(s) utilize radio waves to sense the presence and position of objects.
[0064] Alternatively, LIDAR(s) transmits light (e.g., ultraviolet, visible, and infrared) at the roads and some of this light is reflected/scattered back by the road surface in the terrain area. This reflected light is received and analysed to determine various attributes of the surface of the terrain area. For example, LIDAR(s) may determine the range/position of the pothole or bumps, or other objects based on the time required for the transmitted light to be reflected back. In addition, LIDAR(s) may detect the surface type and/or other properties of the road surface based on the intensity of the reflected light.
[0065] In alternate implementations, the terrain detection system 100 may or may not include other sensor(s) to detect various attributes of the environment surrounding the vehicle. Sensors include a temperature sensor configured to determine the outside temperature and a rain detector configured to detect the accumulated rain on the vehicle. It will be appreciated that alternative embodiments may include other types of sensors as well.
[0066] In accordance with an embodiment of the present invention, the terrain detecting system 100 may also include a navigation system to generate data describing the current position of the electric vehicle 122. In one embodiment, the navigation system includes a global positioning system (GPS) and/or one or more inertial measurement units (IMUs) for determining the current coordinates of the electric vehicle 122 based on received GPS signals and/or dead reckoning techniques. The current coordinates of vehicle 122 may be utilized to identify the current location of vehicle 122 on a map that is stored in the database 102.
[0067] The user device 112 is anyone of a desktop computer, a laptop computer, a user computer, a tablet computer, a personal digital assistant (PDA), a cellular telephone, a communication network appliance, a camera, a smartphone, an enhanced general packet radio service (EGPRS) mobile phone, a media player, a navigation device, an email device, a game console, or a combination of any these data processing devices or other data processing devices. Furthermore, the user device 112 may be provided access to and/or receive application software executed and/or stored on any of the remote server.
[0068] In some examples, the user device 112 performs functions of a social communication network (not shown) to the virtual platform 104. In some implementations, the user device 112 may communicate wirelessly through a communication interface, which may include digital signal processing circuitry where necessary.
[0069] Fig. 2 is a block diagram illustrating different terrain detection electronic control units (ECU) 111 in accordance with an embodiment of the present invention. The terrain detection electronic control units (ECU) 111 includes the gradient detection unit 205, the coefficient of friction unit 210, the bump and pothole detection unit 215, the surface detection unit 220 or a combination thereof.
[0070] The gradient detection unit 205 is configured to calculate gradient of road by determining a state observer, an accelerometer readings, and an estimated accelerations, scaling and rotating the accelerometer reading and a gyroscope reading from an IMU reference frame to a vehicle reference frame, correcting the accelerometer reading by measuring a vehicle speed at a steady state and removing scaling, determining an euler angle from the gyroscope readings by the state observer and correcting the euler angle by calculating difference between the accelerometer readings and estimated accelerations to get the gradient of the road.
[0071] The vehicle speed along with gyroscope readings is used as an input to the state observer. Further, the vehicle speed is calculated by the motor encoder and the wheel speed sensor.
[0072] In an embodiment of the present invention, the vehicle pitch of the electric vehicle (122) may be equal to road gradient.
[0073] In different implementations of the present invention, the gradient detection unit (205) is operably configured to activate and/or deactivate hill assisting conditions.
[0074] Referring to Fig. 2A illustrating an exemplary plot between speed and gradient of the electric vehicle 122 for calculating a gradient of the slope. The gradient detection is tested by taking the electric vehicle 122 on a slope and stopping the gradient estimation by the electric vehicle 122 when it is found to be equal to the actual measured gradient of the slope.
[0075] The coefficient of friction unit 210 is configured to estimate coefficient of friction of road by measuring a vehicle acceleration and a speed profile of the electric vehicle 122, applying a motor torque and a brake pressure to the electric vehicle 122 the state observer to model behavior of the electric vehicle 122 over surfaces having different coefficients of friction, calculating an expected vehicle speed of the electric vehicle 122 based on the behavior of the electric vehicle 122 over surfaces having different coefficients of friction, and comparing measured vehicle speed from the motor encoder and wheel speed sensor with the expected vehicle speed to estimate the coefficient of friction.
[0076] The motor torque and the brake pressure determines a total tractive force applied to the electric vehicle 122 and, the expected vehicle acceleration and the speed profiles of the electric vehicle 122 is determined with the help of a mass estimate of the electric vehicle 122.
[0077] The estimated coefficient of friction may be used for launch control, traction control, yaw stability control and ABS.
[0078] The bump and pothole detection unit 215 is configured to detect bumps and potholes on roads by determining a change of orientation of the electric vehicle 122 along with accelerations of the electric vehicle 122 based on sensor readings from an accelerometer, a gyroscope, the motor encoder and the wheel speed sensors, transforming the sensor readings to the vehicle reference frame to obtain longitudinal accelerations and vertical accelerations of the electric vehicle 122, deriving a vehicle pitch for the electric vehicle 122 based on the state observer, the accelerometer readings, and the estimated accelerations, storing a historical data of the vehicle pitch of the electric vehicle 122 on a controller for “N” vehicle pitches; where N is a positive integer, analyzing the peaks formed by the historical data of the electric vehicle 122 at different frequencies depending on vehicle speed using a fast fourier transform and comparing the vehicle speed of the electric vehicle 122 with a predicted profile of bumps and potholes to determine whether bumps and potholes are detected on the terrain of the electric vehicle 122.
[0079] In accordance with one embodiment of the present invention, the peak formed at a low frequency compared to the vehicle speed indicates bump or pothole is detected.
[0080] In accordance with one embodiment of the present invention, the peak formed at a high frequency compared to the vehicle speed indicates no bump or pothole is detected.
[0081] In different implementations of the present invention, the wheel speed sensor data acquired from the wheel speed sensor is compared to the speed profiles of the electric vehicle 122 on bumps and potholes to detect if there are any bumps or potholes on the road.
[0082] Further, the bump and pothole detection unit 215 may also be configured to track vehicle suspension health and a rider behavior.
[0083] The surface detection unit 220 is configured to detect the surface of roads including topography of the road, depressions or steps, smooth/flat road segments, road type, road markings, road conditions, and other road surface features. In one embodiment, the road surface type may be identified as concrete, asphalt, pavement, gravel, grass, etc. for the detected road. Alternatively, the surface detection unit 220 may detect oil, standing-water, ice, snow, and other materials on the detected road. This information may be utilized to determine the surface condition (e.g., dry, wet, icy, oily, etc.) of the detected road.
[0084] Fig. 3 is a flowchart illustrating a method to detect a type of terrain travelled by an electric vehicle 300 in accordance with an embodiment of the present invention. In particular, the type of terrain is detected by a terrain detection electronic control unit (ECU) 111.
[0085] At step 305, a terrain data of roads is received by a plurality of terrain sensors 114 on an electric vehicle 122. The plurality of terrain sensors 114 includes a motor encoder, an Inertial measurement unit IMU sensor, a wheel speed sensor and the like.
[0086] At step 310, at least one road surface properties including gradient of road, coefficient of friction of road, bumps and potholes on road are analysed based on obtained terrain data. A gradient detection unit 205 calculates a gradient of road, a coefficient of friction unit estimates a coefficient of friction of the road, a bump and pothole detection unit detects bumps and potholes on roads and a surface detection unit detects the surface of roads.
[0087] At step 315, the terrain detection electronic control unit (ECU) 111 determines a type of terrain based on the at least one road surface properties. The type of terrain is any but not limited to an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
[0088] Fig. 4 is a flowchart 400 illustrating a method to calculate gradient of road in accordance with an embodiment of the present invention. The gradient of the road is calculated by the gradient detection unit 205. The method starts at step 405 and proceeds till step 425.
[0089] At step 405, a state observer, an accelerometer readings, and estimated accelerations are determined. In particular, the state observers are an established concept in control theory. Firstly, the vehicle speed is estimated using the motor encoder and wheel speed sensor. The vehicle speed estimate along with gyroscope readings is used as an input to the observer. Further, the accelerometer readings are used as a measurement to correct the observer.
[0090] At step 410, the accelerometer reading, and a gyroscope reading are scaled and rotated from an IMU reference frame to a vehicle reference frame.
[0091] At step 415, the accelerometer readings tend to have scaling compared to gravity which are corrected by measuring a vehicle speed at a steady state and removing the scaling.
[0092] At step 420, an euler angle is determined from the gyroscope readings by the state observer.
[0093] At step 425, the euler angle is corrected by calculating the difference between the accelerometer readings and estimated accelerations to get the gradient of the gradient.
[0094] In accordance with an embodiment of the present invention, the pitch is estimated by the electric vehicle 122 is equal to the road gradient.
[0095] Fig. 5 is a flowchart 500 illustrating a method to calculate the coefficient of friction in accordance with an embodiment of the present invention. The coefficient of friction of the road is estimated by the coefficient of friction unit (210). The method starts at step 505 and proceeds till step 525.
[0096] At step 505, a vehicle acceleration and a speed profile of the electric vehicle 122 is measured. In particular, the expected vehicle acceleration and the speed profiles of the electric vehicle 122 is determined with the help of a mass estimate of the electric vehicle 122.
[0097] At step 510, a motor torque and a brake pressure are applied to the electric vehicle 122 the state observer to model behavior of the electric vehicle 122 over surfaces having different coefficients of friction. In particular, the motor torque and the brake pressure determine a total tractive force applied to the electric vehicle 122.
[0098] At step 515, an expected vehicle speed of the electric vehicle 122 is calculated based on the behavior of the electric vehicle 122 over surfaces having different coefficients of friction.
[0099] At step 520, the measured vehicle speed from the motor encoder and wheel speed sensor is compared with the expected vehicle speed to estimate the coefficient of friction.
[00100] Fig. 6 is a flowchart 600 illustrating a method to detect bump and pothole on roads in accordance with an embodiment of the present invention. The bump and pothole on roads are detected by the bump and pothole detection unit 215.
[00101] At step 605, a change of orientation of the electric vehicle 122 is determined along with accelerations of the electric vehicle 122 based on a sensor reading from an accelerometer, a gyroscope, the motor encoder and the wheel speed sensor.
[00102] At step 610, the sensor readings are transformed to the vehicle reference frame to obtain longitudinal accelerations and vertical accelerations of the electric vehicle 122.
[00103] At step 615, the vehicle pitch is derived for the electric vehicle 122 based on the state observer, the accelerometer readings, and estimated accelerations.
[00104] At step 620, a historical data of the vehicle pitch of the electric vehicle 122 is stored on a controller for “N” vehicle pitches, wherein N is a positive integer.
[00105] At step 625, peaks formed by the historical data of the electric vehicle at different frequencies depending on vehicle speed are analysed using a Fast Fourier transform.
[00106] The peak formed at a low frequency compared to the vehicle speed indicates a bump or pothole is detected.
[00107] The peak formed at a high frequency compared to the vehicle speed indicates a bump or pothole is detected.
[00108] At step 630, the vehicle speed of the electric vehicle 122 is compared with the predicted profiles to determine whether bumps and potholes are detected on the terrain of the electric vehicle 122.
[00109] In accordance with various embodiments of the present invention, the outputs of terrain detection may be used as an input to other rider assistance features.
[00110] While the preferred embodiments and best modes of utilizing the present invention have been disclosed above, other variations are also possible. For example, the structural components of salt level sensing devices are preferably formed of a non-corrosive, sealable, insulating plastic material for use with water softeners, any other suitable rigid material, such as a metal, could be used.
[00111] While the detailed description has shown, described, and pointed out novel features as applied to various alternatives, it can be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the scope of the disclosure. As can be recognized, certain alternatives described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others.
[00112] The disclosures and the description herein are intended to be illustrative and are not in any sense limiting the invention, defined in scope by the following claims.

, Claims:We Claim,
1. A method (300) to detect a type of terrain surrounding an electric vehicle (122) by a terrain detection electronic control unit (ECU) (111), wherein the method comprising steps of:
receiving, a terrain data of roads by a plurality of terrain sensors (114) on the electric vehicle (122);
analyzing, at least one road surface properties including a gradient of road, a coefficient of friction of road, bumps and potholes on the road based on obtained terrain data, wherein,
a gradient detection unit (205) configured to calculate the gradient of road;
a coefficient of friction unit (210) configured to estimate the coefficient of friction of road;
a bump and pothole detection unit (215) configured to detect bumps and potholes on the road;
a surface detection unit (220) configured to detect surface of road;
determining, by the terrain detection electronic control unit (ECU) (111), the type of terrain based on the at least one road surface properties.
2. The method (300) as claimed in claim 1, wherein the plurality of terrain sensors (114) includes a motor encoder, an Inertial measurement unit (IMU) sensor, a wheel speed sensor.
3. The method (300) as claimed in claim 1, wherein the type of terrain is any one of an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
4. The method (300) as claimed in claim 1, wherein the electric vehicle (122) is any of a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a Plug-in Hybrid electric vehicle (PHEV) Fuel Cell electric vehicle (FCEV), a two wheeler electric bike, a three wheeler electric vehicle.
5. The method (300) as claimed in claim 1, wherein a user device (112) is configured with an input interface that is anyone of a smartphone, a laptop, a dashboard, or a button placed on the electric vehicle (122).
6. The method (300) as claimed in claim 1, wherein the method (300) further comprises a step of providing and/or improving rider assistance based on the plurality of road surface properties.
7.The method (300) as claimed in claim 1, wherein the gradient detection unit (205) calculates gradient of road by:
determining a state observer, accelerometer readings, and estimated accelerations;
scaling and rotating an accelerometer reading and a gyroscope reading from an IMU reference frame to a vehicle reference frame;
correcting the accelerometer reading by measuring a vehicle speed at a steady state and removing scaling;
determining an euler angle from the gyroscope readings by the state observer;
correcting the euler angle by calculating difference between the accelerometer readings and estimated accelerations to get the gradient.
8. The method (400) as claimed in claim 7, wherein the vehicle speed along with gyroscope readings is used as an input to the state observer.
9. The method (400) as claimed in claim 7, wherein the vehicle speed is calculated by the motor encoder and the wheel speed sensor.
10. The method (300) as claimed in claim 1, wherein a vehicle pitch of the electric vehicle (122) is equal to road gradient.
11.The method (300) as claimed in claim 1, wherein the coefficient of friction unit (210) calculates an estimated coefficient of friction of road by:
measuring a vehicle acceleration and a speed profile of the electric vehicle (122);
applying a motor torque and a brake pressure to the electric vehicle (122) the state observer to model behavior of the electric vehicle (122) over surfaces having different coefficients of friction;
calculating an expected vehicle speed of the electric vehicle (122) based on the behavior of the electric vehicle (122) over surfaces having different coefficients of friction;
comparing measured vehicle speed from the motor encoder and wheel speed sensor with the expected vehicle speed to estimate the coefficient of friction.
12.The method (300) as claimed in claim 1, the bump and pothole detection unit (215) detects bump and pothole on roads by:
determining a change of orientation of the electric vehicle (122) along with accelerations of the electric vehicle (122) based on sensor readings from an accelerometer, a gyroscope, the motor encoder and the wheel speed sensors;
transform the sensor readings to the vehicle reference frame to obtain longitudinal accelerations and vertical accelerations of the electric vehicle (122);
deriving the vehicle pitch for the electric vehicle (122) based on the state observer, the accelerometer readings, and estimated accelerations;
storing a vehicle pitch data of the electric vehicle (122) on a controller for “N” vehicle pitches; where N is a positive integer;
analyzing the peaks formed by the vehicle pitch data of the electric vehicle (122) at different frequencies depending on vehicle speed using a fast fourier transform;
comparing the vehicle speed of the electric vehicle (122) with a predicted profile to determine whether bumps and potholes are detected on the terrain of the electric vehicle (122).
13.The method (600) as claimed in claim 12, wherein the peak is formed at a low frequency compared to the vehicle speed indicates bump or pothole is detected.
14.The method (600) as claimed in claim 12, wherein the peak is formed at a high frequency compared to the vehicle speed indicates no bump or pothole is detected.
15.The method (600) as claimed in claim 12, wherein a wheel speed sensor data acquired from the wheel speed sensor is compared to the speed profiles of the electric vehicle on bumps and potholes to detect the bump or pothole.
16.The method (600) as claimed in claim 12, wherein the bump and pothole detection unit (215) is further configured to track vehicle suspension health and a rider behavior.
17.The method (500) as claimed in claim 12, wherein the motor torque and the brake pressure determine a total tractive force applied to the electric vehicle (122).
18.The method (500) as claimed in claim 11, wherein the expected vehicle acceleration and the speed profiles of the electric vehicle (122) is determined with the help of a mass estimate of the electric vehicle (122).
19.The method (400) as claimed in claim 7, wherein the gradient detection unit (205) is operably configured to activate and/or deactivate a hill assisting module.
20.A terrain detecting system (100) for use with an electric vehicle (122) to detect a type of a terrain comprising:
a user device (112), to display the plurality of road surface properties including a gradient of road, a coefficient of friction of road, bumps and potholes on road the electric vehicle (122) is traveling through;
a virtual platform (104) having a plurality of databases (102) and memory (106) to store data;
a processor (110) is operably configured with a terrain detection electronic control units (ECU) (111) and a plurality of modules (107) to execute one or more instructions preferably stored within the memory (106);
a plurality of terrain sensors (114) configured to obtain a terrain data of roads to be travelled by the electric vehicle (122);
the terrain detection electronic control units (ECU) (111) configured to detect the type of terrain, wherein the terrain detection electronic control units (ECU) (111) includes a gradient detection unit (205) configured to calculate the gradient of road, a coefficient of friction unit (210) configured to estimate the coefficient of friction of road, a bump and pothole detection unit (215) configured to detect bumps and potholes on roads, a surface detection unit (220) configured to detect surface of roads; and
a communication network (108) configured to allow communication between the virtual platform (104), the plurality of databases (102), the user device (112), the terrain detection electronic control units (ECU) (111).
21.The terrain detection system (100) as claimed in claim 20, wherein the detection electronic control units (ECU) (111) is configured to:
obtain, a terrain data of roads by the plurality of terrain sensors (114) on the electric vehicle (122);
determine, at least one road surface properties including gradient of road, coefficient of friction of road, bumps and potholes on road based on obtained terrain data,
detect electronic control unit (ECU) (111), the type of terrain based on the at least one road surface properties.
22.The terrain detection system (100) as claimed in claim 20, wherein the type of terrain is any one of an uphill, a flat ground, a muddy ground, a barren land or a down-hill, and alike.
23. The terrain detection system (100) as claimed in claim 20, wherein the virtual platform (104) is either of a cloud server or the electric vehicle (122).
24.The terrain detection system (100) as claimed in claim 20, wherein the plurality of terrain sensors (114) includes a motor encoder, an Inertial measurement unit (IMU) sensor, a wheel speed sensor.
25.The terrain detection system (100) as claimed in claim 20, wherein the electric vehicle (122) is any of a battery electric vehicle (BEV), a hybrid electric vehicle (HEV), a Plug-in Hybrid electric vehicle (PHEV) Fuel Cell electric vehicle (FCEV), a two wheeler electric bike, a three wheeler electric vehicle.
26.The terrain detection system (100) as claimed in claim 20, wherein the user device (112) is configured with an input interface that is anyone of a smartphone, a laptop, a dashboard, or a button placed on the electric vehicle (122).
27.The terrain detection system (100) as claimed in claim 20, wherein the gradient detection unit (205) calculates gradient of road by:
determining a state observer, accelerometer readings, and estimated accelerations;
scaling and rotating an accelerometer reading and a gyroscope reading from an IMU reference frame to a vehicle reference frame;
correcting the accelerometer reading by measuring a vehicle speed at a steady state and removing scaling;
determining an euler angle from the gyroscope readings by the state observer;
correcting the euler angle by calculating difference between the accelerometer readings and estimated accelerations to get the gradient.
28. The terrain detection system (100) as claimed in claim 27, wherein the vehicle speed along with gyroscope readings is used as an input to the state observer.
29.The terrain detection system (100) as claimed in claim 27, wherein the vehicle speed is calculated by the motor encoder and the wheel speed sensor.
30.The terrain detection system (100) as claimed in claim 20, wherein a vehicle pitch of the electric vehicle (122) is equal to road gradient.
31.The terrain detection system (100) as claimed in claim 20, wherein the coefficient of friction unit (210) calculates an estimated coefficient of friction of road by:
Measuring, a vehicle acceleration and a speed profile of the electric vehicle (122);
applying, a motor torque and a brake pressure to the electric vehicle (122) the state observer to model behavior of the electric vehicle (122) over surfaces having different coefficients of friction;
calculating, an expected vehicle speed of the electric vehicle (122) based on the behavior of the electric vehicle (122) over surfaces having different coefficients of friction;
comparing, measured vehicle speed from the motor encoder and wheel speed sensor with the expected vehicle speed to estimate the coefficient of friction.
32.The terrain detection system (100) as claimed in claim 20, wherein the bump and pothole detection unit (215) detect bump and pothole on roads by:
determining a change of orientation of the electric vehicle (122) along with accelerations of the electric vehicle (122) based on sensor readings from an accelerometer, a gyroscope, the motor encoder and the wheel speed sensors;
transform the sensor readings to the vehicle reference frame to obtain longitudinal accelerations and vertical accelerations of the electric vehicle (122);
deriving the vehicle pitch for the electric vehicle (122) based on the state observer, the accelerometer readings, and estimated accelerations;
storing a vehicle pitch data of the electric vehicle (122) on a controller for “N” vehicle pitches; where N is a positive integer;
analyzing the peaks formed by the vehicle pitch data of the electric vehicle (122) at different frequencies depending on vehicle speed using a fast fourier transform;
comparing the vehicle speed of the electric vehicle (122) with a predicted profile to determine whether bumps and potholes are detected on the terrain of the electric vehicle (122).
33.The terrain detection system (100) as claimed in claim 32, wherein the peak is formed at a low frequency compared to the vehicle speed indicates bump or pothole is detected.
34.The terrain detection system (100) as claimed in claim 32, wherein the peak is formed at a high frequency compared to the vehicle speed indicates no bump or pothole is detected.
35.The terrain detection system (100) as claimed in claim 32, wherein a wheel speed sensor data acquired from the wheel speed sensor is compared to the speed profiles of the electric vehicle (122) on bumps and potholes to detect the bump or pothole.
36.The terrain detection system (100) as claimed in claim 32, wherein the bump and pothole detection unit (215) is further configured to track vehicle suspension health and a rider behavior.
37.The terrain detection system (100) as claimed in claim 20, wherein the motor torque and the brake pressure determine a total tractive force applied to the electric vehicle (122).
38.The terrain detection system (100) as claimed in claim 31, wherein the vehicle acceleration and the speed profiles of the electric vehicle (122) is determined with the help of a mass estimate of the electric vehicle (122).
39.The terrain detection system (100) as claimed in claim 27, wherein the gradient detection unit (205) is operably configured to activate and/or deactivate hill assisting module.