Description:TECHNICAL FIELD

[001] The present disclosure generally relates to the field of electric vehicles and more particularly to a system and a method for setting the performance parameters of a vehicle.

BACKGROUND

[002] Vehicles equipped with different driving modes are becoming increasingly popular because such vehicles offer riders the ability to tailor their riding experience to various road conditions, riding styles and personal preferences. The driving modes of a vehicle are generally preconfigured with different torque, acceleration and regenerative braking profiles that optimize various aspects of the vehicle’s performance, such as power, transmission behavior, regenerative braking, and traction control, etc. Exemplary driving modes include Normal, Eco, Sports, etc., and such modes are accessible through a button, a knob, or a menu on an interface for allowing the rider to switch between Normal, Eco, and Sports modes, among others. Such driving modes enable the riders to adapt their vehicles to different driving conditions. For instance, the Sport mode may deliver more aggressive acceleration and handling characteristics, while the Eco mode may prioritize efficiency and range on the available fuel or charge in the battery, by reducing engine or motor power.

[003] Even though the vehicles with driving modes offer versatility and control, the conventional vehicles present several challenges and problems. One of the primary problems with conventional vehicles with driving modes is the potential for rider confusion. For example, a rider may advertently or inadvertently choose an inappropriate driving mode, and this may result in loss of performance of the vehicle and may lead to unexpected and unsafe outcomes. In another example, considering an electric vehicle with different driving modes, choosing a driving mode with an inappropriate regenerative braking profile may lead to reduced efficiency and discomfort to the rider due to unpredictable braking.

[004] Moreover, riders’ emotional state, physical state, and the ride performance are interdependent. That is, the emotional state, excitation, or exhaustion of the rider, for example, has a significant impact on the physical reaction of the rider while riding, and hence on how the rider rides the vehicle and on the ride performance. If the rider chooses an inappropriate driving mode or regenerative braking profile, the ride may be one or more of stressful, anxious, tiring, irritated, confused, and boring, which in turn affects the riding behaviour and hence the overall ride performance. This may also affect the rider’s ability to react to potential hazards and make safe decisions. For example, riding a vehicle in a sports mode while the rider is anxious may lead to unexpected and unsafe outcomes due to panic reactions. In another example, emotional stress may lead to physical reactions, such as increased heart rate, muscle tension, and adrenaline release. These physiological responses may affect the rider’s ability to control the vehicle effectively resulting in underperformance of the vehicle.

[005] As described, the emotional state and excitation of the rider has a significant impact on how the rider rides and hence on the performance of the vehicle. However, the conventional vehicles equipped with driving modes do not account for the rider’s emotional state, while riding the vehicle which dictates the riding behaviour and hence the overall performance of the vehicle and rider experience. This often leads to a suboptimal performance of the vehicle, for example, reduced efficiency, excessive wear and tear, brake and tyre wear, engine, or motor overheating, etc. This further leads to bad riding experiences, unexpected and unsafe outcomes reducing the overall riding experience.

BRIEF SUMMARY

[006] This summary is provided to introduce a selection of concepts in a simple manner that is further described in the detailed description of the disclosure. This summary is not intended to identify key or essential inventive concepts of the subject matter nor is it intended for determining the scope of the disclosure.

[007] To overcome or mitigate at least one of the problems mentioned above, there exists a need for a system and a method for setting performance parameters of a vehicle based on the emotional state of the rider of the vehicle.

[008] Thus, disclosed is a method for setting performance parameters of a vehicle based on the emotional state of the rider of the vehicle. The method comprises, receiving, by a network interface module, a value of each of one or more physiological parameters of a plurality of physiological parameters of a rider of a vehicle, each value measured by one or more physiological sensors, determining, by a deviation computation module, a deviation of each measured value of each physiological parameter from respective thresholds, determining, by a scoring module, a score for each physiological parameter based on the deviation, determining, by an emotional scoring module, an emotional score based on the scores of each physiological parameter, recommending to the rider, by a recommendation module, one or more operational modes from a plurality of operational modes, based on the determined emotional score and a current operational mode of the vehicle, for setting one or more values for one or more performance parameters of the vehicle defining each operational mode, and setting, by an electronic control unit, the one or more values for the one or more performance parameters of the vehicle automatically or based on a selection of an operational mode from the one or more operational modes recommended to the rider.

[009] Further, disclosed is a system for setting performance parameters of a vehicle based on the emotional state of the rider of the vehicle. The system comprises, one or more physiological sensors, each physiological sensor configured for measuring a value of each physiological parameter of a plurality of physiological parameters of a rider of a vehicle, a controller communicatively connected to the one or more physiological sensors, the controller comprising, a network interface module configured for receiving the value of each physiological parameter of the plurality of physiological parameters, a deviation computation module configured for determining a deviation of each measured value of each physiological parameter from respective thresholds, a scoring module configured for determining a score for each physiological parameter based on the deviation, an emotional scoring module configured for determining an emotional score for the rider based on the scores of each physiological parameter, and a recommendation module configured for recommending to the rider, one or more operational modes from a plurality of operational modes, based on the determined emotional score and a current operational mode of the vehicle, for setting one or more values for one or more performance parameters of the vehicle defining each operational mode, and an electronic control unit communicatively connected to the controller, configured for setting the one or more values for the one or more performance parameters of the vehicle automatically or based on a selection of an operational mode from the one or more operational modes recommended to the rider.

[0010] To further clarify advantages and features of the present disclosure, a more particular description of the disclosure will be rendered by reference to specific embodiments thereof, which is illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting of its scope. The disclosure will be described and explained with additional specificity and detail with the accompanying figures.

BRIEF DESCRIPTION OF THE FIGURES

[0011] The disclosed method and system will be described and explained with additional specificity and detail with the accompanying figures in which:

[0012] Figure 1 illustrates an exemplary electric vehicle, and the vehicle’s charging and other infrastructure;

[0013] Figure 2 shows a block diagram of a system for setting performance parameters of a vehicle based on the emotional state of a rider of the vehicle in accordance with an embodiment of the present disclosure;

[0014] Figure 3 illustrates a method of determining the emotional score for a rider in accordance with an embodiment of the present disclosure; and

[0015] Figure 4 illustrates a method of recommending one or more operational modes to the rider in accordance with an embodiment of the present disclosure.

[0016] Further, persons skilled in the art to which this disclosure belongs will appreciate that elements in the figures are illustrated for simplicity and may not have been necessarily drawn to scale. Furthermore, in terms of the construction of the joining ring and one or more components of the bearing assembly may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.

DETAILED DESCRIPTION

[0017] For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the various embodiments and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the present disclosure is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the present disclosure as illustrated therein being contemplated as would normally occur to one skilled in the art to which the present disclosure relates.

[0018] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the present disclosure and are not intended to be restrictive thereof.

[0019] Whether or not a certain feature or element was limited to being used only once, it may still be referred to as “one or more features” or “one or more elements” or “at least one feature” or “at least one element.” Furthermore, the use of the terms “one or more” or “at least one” feature or element do not preclude there being none of that feature or element, unless otherwise specified by limiting language including, but not limited to, “there needs to be one or more…” or “one or more elements is required.”

[0020] Reference is made herein to some “embodiments.” It should be understood that an embodiment is an example of a possible implementation of any features and/or elements of the present disclosure. Some embodiments have been described for the purpose of explaining one or more of the potential ways in which the specific features and/or elements of the proposed disclosure fulfil the requirements of uniqueness, utility, and non-obviousness.

[0021] Use of the phrases and/or terms including, but not limited to, “a first embodiment,” “a further embodiment,” “an alternative embodiment,” “one embodiment,” “an embodiment,” “multiple embodiments,” “some embodiments,” “other embodiments,” “further embodiment”, “furthermore embodiment”, “additional embodiment” or other variants thereof do not necessarily refer to the same embodiments. Unless otherwise specified, one or more particular features and/or elements described in connection with one or more embodiments may be found in one embodiment, or may be found in more than one embodiment, or may be found in all embodiments, or may be found in no embodiments. Although one or more features and/or elements may be described herein in the context of only a single embodiment, or in the context of more than one embodiment, or in the context of all embodiments, the features and/or elements may instead be provided separately or in any appropriate combination or not at all. Conversely, any features and/or elements described in the context of separate embodiments may alternatively be realized as existing together in the context of a single embodiment.

[0022] Any particular and all details set forth herein are used in the context of some embodiments and therefore should not necessarily be taken as limiting factors to the proposed disclosure.

[0023] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by “comprises... a” does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

[0024] Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.

[0025] For the sake of clarity, the first digit of a reference numeral of each component of the present disclosure is indicative of the Figure number, in which the corresponding component is shown. For example, reference numerals starting with digit “1” are shown at least in Figure 1. Similarly, reference numerals starting with digit “2” are shown at least in Figure 2.

[0026] Embodiments of the present disclosure disclose a system and a method for setting performance parameters of a vehicle based on the emotional state of the rider of the vehicle. Initially, a controller receives a value of each of one or more physiological parameters of a plurality of physiological parameters of a rider of a vehicle from a plurality of sensor and determines a deviation of each measured value of each physiological parameter from respective predefined thresholds. Then the controller determines a score for each physiological parameter based on the deviation. The controller then determines an emotional score based on the scores of each physiological parameter and recommends one or more operational modes of the vehicle from a plurality of operational modes to the rider, based on the determined emotional score and a current operational mode of the vehicle, for setting one or more values for one or more performance parameters of the vehicle defining each operational mode. Then, in one implementation, an electronic control unit (ECU) communicatively connected to the controller, automatically sets the one or more values for the one or more performance parameters of the vehicle defining an operational mode from one or more operation modes. That is, the ECU sets the vehicle to one of the one or more operational modes. In another implementation, the ECU waits for a selection of an operational mode from the one or more operational modes recommended to the rider and sets the one or more values for the one or more performance parameters of the vehicle defining the selected operational mode based on rider’s selection.

[0027] The vehicle as described herein may include but not limited to, electric vehicles, internal combustion engine vehicles, and hybrid vehicles, and may have one or more wheels. However, the features, the functions and the elements of the proposed system and method are described in the context of an electric vehicle as an example. The electric vehicle (EV) as described herein may include, but not limited to, scooters, mopeds, motorcycles, three-wheelers such as auto-rickshaws, four-wheelers such as cars and other Light Commercial Vehicles (LCVs) and Heavy Commercial Vehicles (HCVs), Heavy Transport Vehicles (HTVs), primarily work on the principle of driving an electric motor using power from the batteries provided in the EV. Furthermore, the electric vehicle may have at least one wheel which is electrically powered to drive such a vehicle. The term ‘wheel’ may refer to any ground-engaging member which allows traversal of the electric vehicle over a path. The types of EVs include Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV) and Range Extended Electric Vehicle. However, the subsequent paragraphs pertain to the different elements of two-wheeled electric vehicles and hereinafter referred to as an electric vehicle or EV, and basic elements and functions of the elements of an exemplary electric vehicle are described below.

[0028] Figure 1 illustrates an exemplary electric vehicle, and the vehicle’s charging and other infrastructure. In construction, the electric vehicle (EV) 100 typically comprises a battery or battery pack 105 enclosed within a battery casing and includes a Battery Management System (BMS), an on-board charger 110, a Motor Controller Unit (MCU), an electric motor 115 and an electric transmission system 120. The primary functions of the above-mentioned elements are detailed in the following paragraphs: The battery of an EV 100 (also known as Electric Vehicle Battery (EVB) or traction battery) is re-chargeable in nature and is the primary source of energy required for the operation of the EV, wherein the battery 105 is typically charged using the electric power from the grid through a charging infrastructure 125. The battery may be charged using Alternating Current (AC) or Direct Current (DC), wherein, in case of AC input, the on-board charger 110 converts the AC power to DC power after which the DC power is transmitted to the battery through the BMS. However, in case of DC charging, the on-board charger 110 may be bypassed, and the current transmitted directly to the battery through the BMS. Additionally, the EV 100 may also be equipped with wireless infrastructure such as, but not limited to Bluetooth, Wi-Fi and so on to facilitate wireless communication with the charging infrastructure 125, other EVs or the cloud.

[0029] The battery 105 is made up of a plurality of cells which are grouped into a plurality of modules in a manner in which the temperature difference between the cells does not exceed 5 °C. The terms “battery”, and “battery pack” may be used interchangeably and may refer to any of a variety of different rechargeable cell compositions and configurations including, but not limited to, lithium-ion (e.g., lithium iron phosphate, lithium cobalt oxide, other lithium metal oxides, etc.), lithium-ion polymer, nickel metal hydride, nickel cadmium, nickel hydrogen, nickel-zinc, silver zinc, or other battery types or configurations. The term “battery pack” as used herein may refer to multiple individual batteries enclosed within a single structure or multi-piece structure. The individual batteries may be electrically interconnected to achieve a desired voltage and current capacity for a desired application. The Battery Management System (BMS) is an electronic system, the primary function of which is to ensure that the battery 105 is operating safely and efficiently. The BMS continuously monitors different parameters of the battery such as temperature, voltage, current and so on, and communicates these parameters to the Electronic Control Unit (ECU) and the Motor Controller Unit (MCU) in the EV using one or more protocols including but not limited to, Controller Area Network (CAN) bus protocol which facilitates the communication between the ECU and MCU and other peripheral elements of the EV 110 without the requirement of a host computer.

[0030] The MCU primarily controls or regulates the operation of the electric motor based on the power transmitted from the vehicle’s battery, wherein the primary functions of the MCU include starting the electric motor 115, stopping the electric motor 115, controlling the speed of the electric motor 115, enabling the vehicle to move in the reverse direction and protect the electric motor 115 from premature wear and tear. The primary function of the electric motor 115 is to convert electrical energy into mechanical energy, wherein the converted mechanical energy is subsequently transferred to the transmission system of the EV to facilitate movement of the EV. Additionally, the electric motor 115 also acts as a generator during regenerative braking (that is, kinetic energy of the EV in motion is converted into electrical energy and stored in the battery of the EV). The types of motors generally employed in EVs include, but are not limited to DC series motor, Brushless DC motor (also known as BLDC motors), Permanent Magnet Synchronous Motor (PMSM), Three Phase AC Induction Motors and Switched Reluctance Motor (SRM).

[0031] The transmission system 120 of the EV 100 facilitates the transfer of the generated mechanical energy by the electric motor 115 to the wheels (130a, 130b) of the EV. Generally, the transmission systems 120 used in EVs include single speed transmission system and multi-speed (i.e., two-speed) transmission system, wherein the single speed transmission system comprises a single gear pair whereby the EV runs at a constant speed ratio between the motor rotational speed and the wheel rotational speed. However, the multi-speed/two-speed transmission system comprises a compound planetary gear system with a double pinion planetary gear set and a single pinion planetary gear set thereby resulting in two different gear ratios which facilitates higher torque and vehicle speed depending on the selected gear ratio.

[0032] In one embodiment, all data pertaining to the EV 100 or charging infrastructure 125 or both, are collected and processed using a remote server (known as cloud) 135, wherein the processed data is indicated to the rider of the EV 100 through a display unit present in the dashboard 140 of the EV 100. In an embodiment, the display unit may be an interactive or touch sensitive display unit. In another embodiment, the display unit may be a non-interactive display unit.

[0033] As described, embodiments of the present disclosure disclose a system and a method for setting performance parameters of a vehicle based on the emotional state of the rider of the vehicle. The system and the method may be implemented with any vehicle; however, the elements and the functions of the proposed system and method are described in the context of the vehicle described in Figure 1.

[0034] Figure 2 shows a block diagram of a system for setting performance parameters of a vehicle based on the emotional state of a rider of the vehicle in accordance with an embodiment of the present disclosure. As shown, the system 200 comprises one or more physiological sensors 205, a controller 210, and an electronic control unit 215, wherein the controller 210 comprises a network interface module 220, a memory module 225, a deviation computation module 230, a scoring module 235, an emotional scoring module 240, a recommendation module 245 and a performance parameter computation module 250. It is to be noted that the controller 210 may be communicatively connected to the one or more physiological sensors 205 and to the electronic control unit (ECU) 215 of the vehicle 100 through wired or wireless infrastructure such as, and not limited to Bluetooth, Wi-Fi, etc.

[0035] In one embodiment of the present disclosure, the one or more physiological sensors 205 are used for measuring emotional data of the rider of the vehicle 100. The one or more physiological sensors 205 may include but not limited to a heart rate sensor, a skin conductance sensor or galvanic skin response (GSR) sensor, a muscle activity sensor, an acceleration sensor, an electroencephalography sensor (EEG sensor), pulse oximeters, breath rate sensor, etc. In one embodiment, the one or more physiological sensors 205 may be placed on the vehicle 100 or one or more wearable devices worn by the rider, for example a helmet or a pair of riding gloves. For example, the skin conductive sensor may be placed on a handlebar of the vehicle 100 for measuring electrical conductance of the skin of the rider in response to emotional or physiological stimuli. In another example, the EEG sensor for measuring the electrical activity of the brain may be embedded in a helmet worn by the rider, the heart rate sensor for measuring the heart rate of the rider and muscle activity sensor for measuring electrical signals generated by the muscles during contraction and relaxation may be embedded in a wrist band to be worn by the rider. In general, the one or more physiological sensors 205 may be positioned on the vehicle 100 or as a wearable sensor on the helmet, gloves, and other headgear, etc., for sensing the physiological parameters of the rider and thereby determining the emotional state of the rider of the vehicle 100.

[0036] The ECU 215 is configured for setting and regulating torque, throttle, and regenerative braking (regen) as part of the powertrain control. Typically, the ECU 215 determines the amount of torque to be delivered by the electric motor(s) 115 based on various factors, including driver input (accelerator pedal position), vehicle speed, and the state of the battery 110. Further, the ECU 215 adjusts the throttle response to match driving conditions and driving modes and controls the regenerative braking system to modulate the amount of regen based on the rider input and the state of the battery 110.

[0037] In one embodiment of the present disclosure, the ECU 215 is configured for setting the one or more values for the one or more performance parameters of the vehicle 100, wherein the one or more performance parameters comprises a torque profile, a throttle map, and a plurality of regenerative braking characteristics of the vehicle 100. In one implementation, the ECU 215 is configured to set the one or more values for the one or more performance parameters of the vehicle 100 automatically on receiving a trigger from the controller 210. In another implementation, the ECU 215 is configured to set the one or more values for the one or more performance parameters of the vehicle 100 based on a selection of an operational mode from the one or more operational modes recommended to the rider.

[0038] In one embodiment of the present disclosure, the controller 210 is configured for recommending one or more operational modes from a plurality of operational modes, based on an emotional state of the rider and a current operational mode of the vehicle, for setting one or more values for the one or more performance parameters of the vehicle defining each operational mode. The emotional state of the rider as described herein refer to one of happy, sad, positive excitement, negative excitement, arousal, aggressive, anxious, alert, drowsy, etc., and the emotional state of the rider is quantitatively determined using the data received from the one or more physiological sensors 205. Further, the one or more performance parameters comprises a torque profile, a throttle map, and a plurality of regenerative braking characteristics of the vehicle 100, and one or more values for one or more performance parameters are assigned based on the emotional state of the rider.

[0039] Furthermore, the plurality of operational modes may include but not limited to, EcoMode, SmartEcoMode, RodeMode, SportMode, WrapMode, and modes related to regenerative intensity such as WeakRegen. MediumRegen, and StrongRegen, etc. It is to be noted that each of the plurality of operational modes refers to a configuration in which the one or more performance parameters are defined, and one or more values are predefined for each of the one or more performance parameters. For example, torque output of an electric vehicle is controlled by adjusting the current levels, the throttle map defines a relationship between the position of the accelerator pedal or hand throttle and the power output of the vehicle, and the regenerative braking may be enabled or disabled for controlling the braking torque. By defining one or more values for the one or more operational parameters mentioned above, each of the operational modes are defined for the vehicle 100. As described, the controller 210 is configured for recommending one or more operational modes from the plurality of operational modes, based on the emotional state of the rider and a current operational mode of the vehicle, and the ECU 215 is configured to set the one or more values for the one or more performance parameters of the vehicle 100 based on a selection of an operational mode from the one or more operational modes recommended to the rider or automatically. The manner in which the controller 210 functions is described below in further detail.

[0040] Referring to Figure 2 illustrates a block diagram of the controller in accordance with an embodiment of the present disclosure. As shown, the controller 210 comprises a network interface module 220, a memory module 225, a deviation computation module 230, a scoring module 235, an emotional scoring module 240, and a recommendation module 245. The network interface module 220 enables communication between the one or more physiological sensors 205, the ECU 215 and the controller 210. The memory module 225 may include volatile and non-volatile memory devices for storing information and instructions to be executed by the one or more modules and for storing temporary variables or other intermediate information during processing. It is to be noted that the controller 210 may be integrated into the vehicle 100 or integrated into a device worn by the rider or implemented in a cloud server. Based on the implementation, the one or more physiological sensors 205, the controller 210 and the ECU 215 are communicatively connected through wired or wireless network or combination of wired and wireless networks.

[0041] As described, the one or more physiological sensors 205, positioned on the vehicle 100 or worn by the rider, measures a value of each of the one or more physiological parameters of the plurality of physiological parameters of the rider of the vehicle 100 and the measured values are sent to the controller 210. In other words, the controller 210 receives the value of each of the one or more physiological parameters through the network interface module 220. For example, the one or more physiological parameters measured may be the heart rate and skin conductivity level of the rider measured using the heart rate sensor and the skin conductivity sensor respectively, and the value associated with the same may be 95 beats per minute and 45 micro-Siemens (µS), respectively. It is to be noted that the physiological parameters and the values in this example are for explanation purposes only. However, measurement of all physiological parameters enhances the efficiency of the proposed system and method.

[0042] On receiving the value of each of the one or more physiological parameters of the plurality of physiological parameters of the rider, the deviation computation module 230 a deviation of each measured value of each physiological parameter from respective thresholds. The thresholds as described herein may be one or more values derived from a baseline, wherein baseline is a resting level of a physiological parameter in an individual when the individual is in a neutral or relaxed state. For example, a threshold for heart rate may be 70 beats per minutes and a threshold for skin conductivity level may be 30 microsiemens, and such baseline and thresholds may be derived from measuring physiological parameters of a plurality of users (training dataset). Such thresholds may be defined as happiness threshold and excitement threshold, for example. However, individuals may show different values for the same physiological parameters for the same emotional state, for example excitation, and hence what constitutes a baseline or threshold may vary from one individual to another. Hence, in one embodiment of the present disclosure, a machine learning model may be used for fine tuning the thresholds for individual riders. Referring to the example, if the measured heart rate is 95 beats per minute and the skin conductivity level is 45 microsiemens, the deviation computation module 230 computes the deviation as +25 beats per minute and +15 µS.

[0043] Then the scoring module 235 determines a score for each physiological parameter based on the deviation, wherein the score quantifies the degree of deviation from the one or more thresholds of the one or more physiological parameters. It is to be noted that the scoring module 235 may use linear scale, normalized scale, categorical scale, expert opinion scale, or any other such scales to determine a score for each of the one or more physiological parameters. For example, considering the linear scale, a score from zero to ten may be assigned for each of the physiological parameters based on the deviation from the one or more respective thresholds. For example, a substantially higher heart rate (above 100) might indicate excitement, while a higher skin conductance score might indicate arousal, and a score is assigned accordingly.

[0044] On computing the score for each physiological parameter, the emotional scoring module 240 computes an emotional score based on the scores of the each of the physiological parameters. In one embodiment, the emotional score is computed as a weighted sum of the individual scores of each physiological parameter, and this provides an aggregated emotional score. For example, the emotional score may be computed as (0.4 * Heart Rate Deviation) + (0.3 * Skin Conductance Deviation).

[0045] Figure 3 illustrates a method of determining the emotional score for a rider in accordance with an embodiment of the present disclosure. As described above and referring to Figure 3, the value of each of one or more physiological parameters are measured using the one or more physiological sensors 205, such as but not limited to, the heart rate sensor, the skin conductivity sensor, muscle activity sensor, acceleration sensor and EEG sensor. Then the measured value is compared with respective thresholds 305 for determining the deviation of each measured value of each physiological parameter from respective thresholds 305. Based on the deviation, a score 310 is assigned for each physiological parameter. As shown, heart rate sensor value is compared with the happiness threshold to determine the happiness score, the skin conductivity sensor value is compared with the excitement threshold to determine the excitement score, and the muscle activity sensor value is compared with the arousal threshold to determine the arousal score. Further, acceleration senor value and the EEG sensor value are compared with a valence threshold to determine a valence score. The valence score as described herein quantifies the positivity or negativity of an emotional experience. Then the emotional scoring module 240 computes the emotional score 315 based on the scores of the each of the physiological parameters, wherein the emotional score may be a value in a range of zero to ten, for example. The scores of various physical parameters indicate the emotional state of the rider. For example, high positive valence and high arousal might represent joy or excitement state of the rider, and low positive valence and low arousal might represent calmness or contentment of the rider. Hence, values of multiple physiological parameters are analyzed to determine the emotional score of the rider.

[0046] Referring to Figure 2, on determining the emotional score for the rider, the recommendation module 245 recommends one or more operational modes from the plurality of operational modes, based on the determined emotional score and a current operational mode of the vehicle 100, for setting one or more values for the one or more performance parameters of the vehicle defining each operational mode.

[0047] In one embodiment of the present disclosure, the recommendation module 245 compares the emotional score with one or more predefined emotional score thresholds, and one or more operational modes among the plurality of operational modes based on a result of comparison. In such an implementation, one or more rules are defined for recommending the one or more operational modes. For example, considering emotional score scale of zero and ten, if the emotional score of the rider is between values four and five, then the recommendation module 245 may recommend a SportMode. Similarly, the recommendation module 245 compares the emotional score of the rider with the one or more predefined emotional score thresholds and recommends one or more operational modes among the plurality of operational modes, such as EcoMode, SmartEcoMode, RodeMode, SportMode, WrapMode, and modes related to regenerative intensity such as WeakRegen, MediumRegen, and StrongRegen, etc. Such recommendations are displayed on a display unit, dashboard 140 of Figure 1of the vehicle 100. It is to be noted that the recommendation module 245 considers the current operational mode of the vehicle 100 before recommending the one or more operational modes to the rider. For example, if the vehicle 100 is running in the SportMode and the mode determined by the recommendation module 245 is the SportMode, then the recommendation module 245 may not recommend the same to avoid unnecessary distractions for the rider. It is to be noted that the thresholds and weightage of the rules are derived from testing with a plurality of riders. That is, the rules are established that connect one or more emotional scores with one or more setting to the one or more performance parameters. Such rules might be based on expert knowledge or derived from data. Further, the same may be fine-tuned for each individual rider using machine learning techniques.

[0048] Figure 4 illustrates a method of recommending one or more operational modes to the rider in accordance with an embodiment of the present disclosure. As described in the present disclosure, based on the emotional score received from the emotional scoring module 240, the recommendation module 245 recommends one or more operational modes to the rider. As described, the recommendation may be rule-based recommendation in which a plurality of rules is defined, and the one or more operational modes are recommended based on a matching criterion. For example, a rule (IsLow) is defined to recommend one or more operational modes (EcoMode) if the emotional score is less than a threshold value defined for this rule. In another example, the operational modes recommended may be a SportMode and a WeakRegen, and the same is displayed on the dashboard 140 (shown in Figure 1) for rider selection. The rider may accept or reject the one or more operational modes recommended by the system. If the rider selects an operational mode, for example the SoprtMode, the ECU 215 sets one or more values for the one or more performance parameters of the vehicle 100 associated with the SoprtMode as shown at block 405. If the rider rejects the recommendations, then no action is taken by the ECU 215. As described in the present disclosure, each of the plurality of operational modes refers to a configuration in which the one or more performance parameters are defined, and one or more values are predefined for each of the one or more performance parameters. Based on the operational mode selected by the rider, the ECU 215 sets values for the one or more operational parameters of the vehicle as per the configuration of that mode. That is, the ECU 215 sets one or more of the torque outputs of the electric vehicle, the throttle map, and regenerative braking characteristics of the vehicle 100.

[0049] In another embodiment of the present disclosure, the ECU 215 is configured to set the one or more values for the one or more performance parameters of the vehicle automatically. In such an implementation, the once the controller 210 determines the one or more operational modes from a plurality of operational modes, the controller 210 triggers the ECU 215 to set the one or more values for the one or more performance parameters accordingly. In such an implementation, the operational mode that is being set may be notified to the rider. As described, the system 200 measures the emotional state of the rider and sets the performance parameters of the vehicle 100 based on the emotional state, or the system 200 recommends the one or more operational modes to the rider to set the performance parameters of the vehicle 100. In one embodiment of the present disclosure, the system 200 measures the emotional score of the rider (for example, the intensity of emotional arousal or emotional stress) with every throttle action and acceleration of the vehicle. If the response of the intensity is within the range expected then the operational mode, regen levels and throttle maps remain same. If the emotional score is higher than the threshold, the ride mode, regen and throttle profiles are tuned accordingly. For example, if the emotional stress/arousal score is lower than the set thresholds for selected operational mode, the torque, regen and throttle profiles are tuned to give quicker acceleration response, higher power output and agile riding experience to make ride more thrilling.

[0050] As described, the recommendation module 245 is configured for recommending the one or more operational modes to the rider based on the emotional state of the rider. In another embodiment, recommending the one or more operational modes among the plurality of operational modes comprises, determining, based on the emotional score, the one or more values for one or more performance parameters of the vehicle, and recommending the one or more operational modes among the plurality of operational modes based on the determined one or more values of the one or more performance parameters. That is, on determining emotional score of the rider, the performance parameter computation module 250 determines one or more values for one or more performance parameters of the vehicle 100 and then the recommendation module 245 recommends the one or more operational modes matching the determined one or more values of the one or more performance parameters.

[0051] In another embodiment of the present disclosure, the recommendation module 245 is configured for recommending the one or more operational modes from the plurality of operational modes based on the emotional score and one or more preferences set by the rider. The user preference as described herein may be an operational mode set by the rider, or one or more profiles set by the rider, the profile defining torque profile, throttle map, regen characteristics, etc. Further the profile may be defined to set a preferred mode during a particular period of the day, day of the week, etc. The rider may set such preferences through the dashboard 140 of the vehicle 100. In such an implementation, recommendation module 245 recommends the one or more operational modes based on the emotional score and the preferences set by the rider. Such preferences help in deriving the thresholds and weightage of the rules. Further, the rider preference may be used for fine-tuning the thresholds.

[0052] As described, the one or more values for the one or more performance parameters may be determined based on the emotional score of the rider. In such an implementation, the on the one or more preferences set by the rider are also considered while determining the one or more values for the one or more performance parameters.

[0053] In one embodiment of the present disclosure, the one more values of the one or more performance parameters of the vehicle are determined using a machine learning model trained using scores of the plurality of physiological parameters and the emotional scores of the plurality of riders. That is, the machine learning model is trained using a dataset that includes scores of the plurality of physiological parameters of the riders and the corresponding values of the one or more performance parameters of the vehicle. Then the performance parameter computation module 250 determines the one more values of the one or more performance parameters of the vehicle are determined using the scores of the one or more physiological parameters of the rider and the machine learning model.

[0054] In another embodiment of the present disclosure, the one more values of the one or more performance parameters of the vehicle are determined using the emotional score of the rider and one of a fuzzy logic and statistical method. In such an implementation, rules are established that connect one or more emotional scores with one or more setting to the one or more performance parameters. Such rules might be based on expert knowledge or derived from data.

[0055] As described, the system and the method disclosed in the present disclosure controls the vehicle based on the emotional state of the rider by adjusting the torque, throttle, and regen profile of the vehicle, based on the emotional state of the rider, to maintain a set emotional state of the rider. As described, the emotional state refers to, but not limited to, happy, sad, positive excitement, negative excitement, arousal, aggressive, anxious, alert, drowsy, etc., and the emotional state of the rider is quantitatively determined using the data received from the one or more physiological sensors. For example, if the rider is feeling stressed or anxious, the system may alter the torque output profile and regen intensity, to make it a substantially smoother and more comfortable ride. Conversely, if the rider is feeling bored and seeking excitement, the system may tune the torque profile and reduce regen braking to provide a more exciting ride.

[0056] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

[0057] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.

List of reference numerals:
Components Reference numerals
Vehicle 100
Battery pack 105
On-board charger 110
Electric motor 115
Transmission system 120
Charging infrastructure 125
Wheels 130a and 130b
Remote server 135
Dashboard 140
System 200
One or more physiological sensors 205
Controller 210
Electronic control unit 215
Network interface module 220
Memory module 225
Deviation computation module 230
Scoring module 235
Emotional scoring module 240
Recommendation module 245
Performance parameter computation module 250

, Claims:1. A method comprising:
receiving, by a network interface module (220), a value of each of one or more physiological parameters of a plurality of physiological parameters of a rider of a vehicle (100), each value measured by one or more physiological sensors (205);
determining, by a deviation computation module (230), a deviation of each measured value of each physiological parameter from respective thresholds;
determining, by a scoring module (235), a score for each physiological parameter based on the deviation;
determining, by an emotional scoring module (240), an emotional score based on the scores of each physiological parameter;
recommending to the rider, by a recommendation module (245), one or more operational modes from a plurality of operational modes, based on the determined emotional score and a current operational mode of the vehicle (100), for setting one or more values for one or more performance parameters of the vehicle (100) defining each operational mode; and
setting, by an electronic control unit (215), the one or more values for the one or more performance parameters of the vehicle (100) automatically or based on a selection of an operational mode from the one or more operational modes recommended to the rider.

2. The method as claimed in claim 1, wherein the one or more performance parameters of the vehicle (100) comprise a torque profile, a throttle map, and a plurality of regenerative braking characteristics.

3. The method as claimed in claim 1, wherein recommending the one or more operational modes among the plurality of operational modes based on the determined emotional score comprises:
comparing the emotional score with one or more predefined emotional score thresholds; and
recommending the one or more operational modes among the plurality of operational modes based on a result of comparison.

4. The method as claimed in claim 1, wherein recommending the one or more operational modes among the plurality of operational modes comprises:
determining, based on the emotional score, the one or more values for one or more performance parameters of the vehicle (100); and
recommending the one or more operational modes among the plurality of operational modes based on the determined one or more values of the one or more performance parameters.

5. The method as claimed in claim 1, wherein the one or more operational modes from a plurality of operational modes are recommended based on the emotional score and one or more preferences set by the rider.

6. The method as claimed in claim 1, wherein the one or more values of the one or more performance parameters of the vehicle (100) are predefined for each of the operational modes among the plurality of operational modes.

7. The method as claimed in claim 1, wherein the one or more values of the one or more performance parameters of the vehicle (100) are determined based on the one or more preferences set by the rider and the emotional score.

8. The method as claimed in claim 1, wherein the one more values of the one or more performance parameters of the vehicle (100) are determined using a machine learning model trained using scores of the plurality of physiological parameters of a plurality of rider and emotional score of the plurality of riders.

9. The method as claimed in claim 1, wherein the one or more values of the one or more performance parameters of the vehicle (100) are determined using the emotional score and one of a fuzzy logic and statistical method.

10. A system (200) comprising:
one or more physiological sensors (205), each physiological sensor configured for measuring a value of each physiological parameter of a plurality of physiological parameters of a rider of a vehicle (100);
a controller (210) communicatively connected to the one or more physiological sensors (205), the controller comprising:
a network interface module (220) configured for receiving the value of each physiological parameter of the plurality of physiological parameters;
a deviation computation module (230) configured for determining a deviation of each measured value of each physiological parameter from respective thresholds;
a scoring module (235) configured for determining a score for each physiological parameter based on the deviation;
an emotional scoring module (240) configured for determining an emotional score for the rider based on the scores of each physiological parameter; and
a recommendation module (245) configured for recommending to the rider, one or more operational modes from a plurality of operational modes, based on the determined emotional score and a current operational mode of the vehicle (100), for setting one or more values for one or more performance parameters of the vehicle (100) defining each operational mode; and
an electronic control unit (215) communicatively connected to the controller (210), configured for setting the one or more values for the one or more performance parameters of the vehicle (100) automatically or based on a selection of an operational mode from the one or more operational modes recommended to the rider.

11. The system (200) as claimed in claim 10, wherein the controller (210) is communicatively connected to dashboard (140).

12. The system (200) as claimed in claim 10, wherein the vehicle (100) is one of an internal combustion engine vehicle, an electric vehicle, and a hybrid vehicle.

13. The system (200) as claimed in claim 10, the controller (210) is integrated into the vehicle (100).

14. The system (200) as claimed in claim 10, wherein the controller (210) is integrated into a device worn by the rider.

15. The system (200) as claimed in claim 10, wherein the controller (210) is implemented in a cloud server.