Field of the invention:
[0001] The present invention relates to a controller to determine driveability/drivability of a vehicle.
Background of the invention:
[0002] A driveability calibration is a crucial and time-taking step in the vehicle development process. The driveability of the vehicle is evaluated by calibration engineers and test drivers from the Original Equipment Manufacturer (OEM). The driveability is mostly evaluated by the feel of the driver and they may not be able to quantify each features. It is very difficult to translate the driver feedback into the engine controller terms for better fine-tuning. This scenario results in the need of standardization of the driveability assessment. Each feature of the driveability is evaluated objectively and then a rating must be provided. There are tools available for this purpose but they are very huge and need a lot of preparation on the vehicle.
[0003] According to a prior art US6079258 a method for analyzing the driving behavior of motor vehicles is disclosed. The method for analyzing the driving behavior of motor vehicle wherein a car's driveability is measured easily on a test stand by conducting tests with an actual vehicle to obtain measurement variables describing driving behavior; then defining at least one rating indicating the car's driveability as a function of one or more measurement variables; then preparing a simulation model to represent dependencies between the individual measurement variables and, in particular, to compute the rating from a set of predefined measurement variables which can be obtained both from the actual vehicle and on a test stand; and then calibrating a dynamic test stand with the use of the simulation model.
Brief description of the accompanying drawings:
[0004] An embodiment of the disclosure is described with reference to the following accompanying drawing,

[0005] Fig. 1 illustrates a controller to determine driveability of a vehicle, according to an embodiment of the present invention.
Detailed description of the embodiments:
[0006] Fig. 1 illustrates a controller to determine driveability of a vehicle, according to an embodiment of the present invention. The vehicle 100 shown is a motorcycle and not limited thereto. The vehicle 100 comprises an engine 102, an Engine Management System (EMS) module 104 to control and operate the engine 102, an optional Anti-lock Braking System (ABS) module 106 to control the braking operation of the vehicle 100 and other parts and components known to a person skilled in the art. The controller 120 as per the present invention is provided to determine driveability of the vehicle 100 in real-time or run-time, i.e. during driving conditions. The controller 120 is connectable to plurality of first sensors 116 (hereinafter referred to as “first sensors” 116) of the vehicle 100, and comprises a model 122 stored in a memory element 118 of controller 120. The controller 120 is adapted to measure plurality of operational parameters from signals received from the first sensors 116. The controller 120 estimate the driveability of the vehicle 100 by using the measured plurality of operational parameters in the model 122, characterized in that, the controller 120 is further adapted to receive at least one operational parameter related to the vehicle 100 from at least one second sensor 124 (hereinafter referred to as “second sensor” 124) of a computing device 110 for the estimation of the driveability of the vehicle 100.
[0007] The computing device 110 is at least one of a smartphone, a tablet, a laptop, a smart watch, a smart fitness band and a mobile communication device.
[0008] The plurality of operational parameters corresponds to parameters of engine 102 and vehicle 100 selected from a group comprising but not limited to a vehicle speed, a vehicle acceleration, a driver demand (throttle position), a gear position, a clutch state and brake state, a gradient of the road and a roll, pitch and yaw rate, and

lateral, longitudinal and vertical acceleration of the vehicle 100 and other parameters affecting or influencing driveability.
[0009] The aforementioned operational parameters are detected or measured from the first sensors 116 mounted or installed within the vehicle 100. The first sensors 116 are selected from a group comprising but not limited to an engine speed sensor, a vehicle speed sensor, a throttle position sensor, a Manifold Air Pressure (MAP) sensor, a lambda sensor, a temperature sensor and the like.
[0010] The model 122 stored in the memory element 118 of the controller 120 is developed using the correlation of signals measured for the plurality of operational parameters. For the development of the model 122, the data is collected across all driving situations (during numerous on-road and off-road test cycles) along with the feedback from experienced test drivers. The model 122 is then trained with all the collected data using Machine Learning (ML) and Artificial Intelligence (AI). A rating is then set for different conditions and combinations of the plurality of operating parameters based on collected data. Each rating is linked or mapped to EMS 104, for optimizing the driveability of the vehicle 100.
[0011] In accordance to an embodiment of the present invention, the driveability characteristics of vehicle 100 is estimated/provided by the model 122 during a calibration process of the EMS 104. Based on the estimation, a decision is taken on altering or optimizing the calibration in real time.
[0012] In accordance to another embodiment of the present invention, the controller 120 is at least one selected from a group comprising, an Electronic Control Unit (ECU) 114 of computing device 110, the Engine Management System (EMS) 104 of the vehicle 100 and a cloud server 112. Thus, the model 122 is stored in the EMS 104, or in the computing device 110 or in the cloud server 112 or in all. In one embodiment, the estimation of driveability is performed in any one of the controller 120. Alternatively, the estimation of the driveability is performed in distributed

manner by at least two controllers 120 comprising the ECU 114, the EMS 104 and the cloud server 112. Before the estimation is done by at least two controllers 120, the measured signals of the plurality of operational parameters are made available to all the controllers 120, in which case the model 122 is stored in a the controllers 120. In the Fig. 1, the model 122 is shown within the computing device 110 for the sake of explanation and must not be understood in limiting sense.
[0013] The computing device 110 is connected to the EMS 104 through an On Board Diagnostics (OBD) port (not shown) or a Controller Area Network (CAN) port (not shown) of the vehicle 100 through a connector 108. The connector 108 is any one selected from a group of wired and wireless means comprising a Universal Serial Bus (USB), a Type-C USB, a Local Area Network (LAN), a Bluetooth, a Wi-Fi, an Infra-Red (IR) and the like. A non-limiting example is OBD to Bluetooth converter/connector 108.
[0014] The driveability rating is displayed in any one of display screen (not shown) of the vehicle 100 and a display screen (not shown) of the computing device 110 based on the estimation of the driveability by the model 122 in the controller 120. In the vehicle 100, the display screen of a navigation/ infotainment system (not shown) is used.
[0015] In one embodiment, the model 122 is stored in the ECU 114 of the computing device 110, which is mounted to the vehicle 100 at a suitable position (such as on handlebar). The ECU 114 is connected to the EMS 104 of the vehicle 100 through the connector 108. During driving, the ECU 114 is adapted to receive all the signals from the first sensors 116 through the connector 108. The ECU 114 also receives the signals from the second sensor 124 in the computing device 110. The ECU 114 now act as the controller 120 which estimates the driveability of the vehicle 100. The driveability rating after the estimation is displayed on the display screen of the computing device 110. Alternatively, the computing device 110 transmits the rating to the EMS 104 and the rating is shown on the display screen

of the vehicle 100. In still another alternative, the drivability rating is shown in the display screen of both the computing device 110 and the vehicle 100.
[0016] In another embodiment, the model 122 is stored in the EMS 104 of the vehicle 100. The EMS 104 is connected to the ECU 114 of the computing device 110. During driving of the vehicle 100, the EMS 104 receives the signals from the first sensors 116 and a second sensor 124 from the ABS module 106. The second sensor 124 is referred to the Inertial Measurement Unit (IMU), which is available in ABS module 106, for the measurement of roll, pitch and yaw rate, and lateral, longitudinal and vertical acceleration of the vehicle 100. However, in the absence or failure of the second sensor 124 in the vehicle 100, the EMS 104 receives the corresponding signals from the second sensor 124 of the computing device 110. The EMS 104 receives the signals through the connector 108. The EMS 104 then acts as the controller 120 and estimates the driveability rating using the model 122. The second sensor 124 in the computing device 110 is at least one of the accelerometer, a gyroscope and the IMU. The driveability rating is then displayed in the display screen as described above.
[0017] In yet another embodiment, the model 122 is stored in the cloud server 112. The cloud server 112 is connected to the EMS 104 through the computing device 110, where the computing device 110 is connected to the cloud through a telecommunication networks 126 (such as 3G, 4G, etc.). The measured signals through the first sensors 116 and the second sensor 124 are transmitted to the cloud server 112 through the computing device 110 via the network 126. The cloud server 112 processes all the received data and transmits back the driveability rating to the computing device 110. The driveability rating is then either displayed in the computing device 110 or in the display screen of the vehicle 100 or both.
[0018] In still yet another embodiment, the processing of the driveability rating of the vehicle 100 is shared between at least two of the controllers 120 comprising the EMS 104, ECU 114 and the cloud server 112.

[0019] In an embodiment of the present invention, an application is installed in the computing device 110 enables the estimation of the driveability and corresponding drivability rating. The application in the computing device 110 provides a Graphical User Interface (GUI) for a user to control operations related to the driveability estimation of the vehicle 100. The user is able to start, stop the estimation of the driveability, diagnose an issue for a specific driveability, report to a service center and the like. The application receives the signals of the EMS 104 via the OBD port and/or CAN port.
[0020] In an embodiment of the present invention, at least one of the plurality of operational parameters which are not detectable (because of unavailability such as in low end motorcycles) of the vehicle 100 are measured by the second sensor 124 of the computing device 110. The second sensor 124 in the computing device 110 is at least one selected from a group comprising an accelerometer, a gyroscope and an Inertial Measurement Sensor (IMU). If the IMU or the accelerometer or the gyroscope is not available in the vehicle 100, then an IMU or the accelerometer or the gyroscope of the computing device 110 (or which are available) is used to measure the corresponding signal. The controller 120 processes the signals from the EMS 104 along with the signal received from the second sensor 124 of the computing device 110. The controller 120 is able to identify the driver demand versus the vehicle response using the first sensors 116, and also measure the road gradient using the second sensor 124. The controller 120 records the data continuously during a driving session. The controller 120 is then configured to extract the required parts (or a test case) of the recorded data for analysis of each feature. Once the data is extracted, each test case is compared against the reference data and a driveability rating is generated. The controller 120 then generates a report possible optimizations to improve driveability.
[0021] In another embodiment, the second sensor 124 which is the IMU is in working condition within the ABS module 106 of the vehicle 100. The EMS 104

receives the signal of the second sensor 124 from the ABS module 106 via CAN and from the computing device 110 via the connector 108. The signal from the computing device 110 is redundant signal, but is still processed together with the signal from the ABS module 106 by the EMS 104 to provide a robust calculation/estimation of the driveability of the vehicle 100. The estimation is also possible to be performed by the ECU 114 and/or the cloud server 112.
[0022] According to an embodiment of the present invention, the controller 120 does not need any additional dedicated instrumentation to be fixed to the vehicle 100, thus eliminates existing tools requiring dedicated hardware and sensors, those are to be mounted on the vehicle 100 before the testing. There is no modification required on the vehicle 100. The present invention provides a simple application as a replacement for the costly driveability evaluation tools. The application also enables to monitor the driving behavior and give intimation to the user. The present invention is usable for the driveability benchmarking of vehicles 100 as well. A driver/rider is able to use a personal computing device 110 (such as phone) with the installed application for the evaluation of driveability rating. The connectivity to the cloud server 112 facilitates advanced data processing, data generation etc. The present invention is applicable for vehicle 100 selected from a group comprising a scooter, a moped, an auto-rickshaw, a car and the like.
[0023] It should be understood that embodiments explained in the description above are only illustrative and do not limit the scope of this invention. Many such embodiments and other modifications and changes in the embodiment explained in the description are envisaged. The scope of the invention is only limited by the scope of the claims.

We claim:
1. A controller (120) to determine driveability of a vehicle (100), said
controller (120) connectable to plurality of first sensors (116) of said vehicle
(100), and comprises a model (122) stored in a memory element (118) of
said controller (120), said controller (120) adapted to
— measure plurality of operational parameters from signals received from said plurality of first sensors (116), and
— estimate driveability of said vehicle (100) by use of said model (122) on the measured plurality of operational parameters, characterized in that
— said controller (120) further adapted to receive at least one operational parameter related to said vehicle (100) from at least one second sensor (124) of a computing device (110) for the estimation of the driveability of said vehicle (100).

2. The controller (120) as claimed in claim 1, is at least one selected from a group comprising, an Electronic Control Unit (ECU) (114) of said computing device (110), an Engine Management System (EMS) (104) of said vehicle (100) and a cloud server (112).
3. The controller (120) as claimed in claim 2, wherein said estimation of driveability is performed in distributed manner by at least two from said group comprising said ECU (114), said EMS (104) and said cloud server (112).
4. The controller (120) as claimed in claim 2, wherein said computing device (110) is connected to said EMS (104) through an On Board Diagnostics (OBD) port via a connector (108).
5. The controller (120) as claimed in claim 4, wherein said connector (108) is any one selected from a group or wired and wireless means comprising a

Universal Serial Bus (USB), a Type-C USB, a Local Area Network (LAN), a Bluetooth, a Wi-Fi, an Infra-Red (IR).
6. The controller (120) as claimed in claim 2, displays a driveability rating based on said estimated driveability in any one of display screen in said vehicle (100) and a display screen of said computing device (110).
7. The controller (120) as claimed in claim 2, wherein said at least one of said plurality of operational parameters which are not detectable in said vehicle (100) are measured by at least one second sensor (124) of said computing device (110).
8. The controller (120) as claimed in claim 1, wherein said computing device (110) is at least one of a smartphone, a tablet, a laptop, a smart watch and a mobile communication device.
9. The controller (120) as claimed in claim 8, wherein an application installed in said computing device (110) enables the estimation of said driveability rating of said vehicle (100).
10. The controller (120) as claimed in claim 1, wherein said at least one second sensor (124) in said computing device (110) is at least one selected from a group comprising an accelerometer, a gyroscope and an Inertial Measurement Sensor (IMU).