DESC:Method and System for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery
FIELD OF INVENTION

[0001] The present invention generally relates to the field of logistics vehicle and more specifically to the field of efficient management and optimization of the operation of the resources involved in the logistics delivery by Electric Vehicle.

BACKGROUND OF THE ART
[0002] The following background discussion includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.

[0003] After nearly a century with the internal combustion engine dominating the personal transportation sector, it now appears that the electric vehicle is on the verge of experiencing rapid growth in both developed and developing vehicle markets. The broad-scale adoption of the electric vehicle could bring significant changes for society in terms of not only the technologies we use for personal transportation, but also moving our economies away from petroleum and lessoning the environmental footprint of transportation.

[0004] Logistics and electric mobility are on rapid increase. Conventional logistics vehicle routing and scheduling methods and systems are designed for Internal Combustion Engine Vehicles (ICEVs). These routing and scheduling method and system ignores constraints of Electric Vehicles (EVs), hence, fails to plan a practical route for the same. Even if some methods and systems exist today, they are static in nature.

[0005] One method can consist of EVs getting allocated based on the first come first serve basis. This method fails to take into account empty legs. This issue can be resolved further by letting vehicle be stationary till next logistic/load, but this method fails to take into account the idle time of the vehicle hence cannot be productive.

[0006] US20020184078A1 provides priority-based allocation methods for use in allocating a vehicle from a fleet of vehicles. The methods provide that a vehicle that is low on fuel, battery charge, or mileage will be given a higher priority for allocation than a vehicle with relatively higher vehicle parameters. Methods include using the vehicle parameter values to directly allocate the vehicles, or indirectly allocate the vehicles using the values to group the vehicles before allocation. Additional indirect methods are provided whereby the vehicle parameter values are used to derive a corresponding numerical value to be used in an algorithm-based allocation method or converted into a percentage for a tier-based allocation method.

[0007] US9201407B2 provides a method and system for Managing electric current allocation of electric vehicle charging stations. A message is received that indicates a request for an allocation of electric current at a first electric vehicle charging station that is connected to a same main electrical circuit breaker as a second electric vehicle charging station that is presently allocated electric current. Responsive to determining that granting the request would exceed a maximum amount of electric current supported by the main electrical circuit breaker, the electric current allocation of at least the second electric vehicle charging station is adjusted such that the request for allocation can be granted and the request is granted and electric current is allocated to the first electric vehicle charging station.

[0008] Zhenhong Lin (2014) Optimizing and Diversifying Electric Vehicle Driving Range for U.S. Drivers. Transportation Science, 48(4):635-650. Properly determining the driving range is critical for accurately predicting the sales and social benefits of battery electric vehicles (BEVs). This study proposes a framework for optimizing the driving range by minimizing the sum of battery price, electricity cost, and range limitation cost—referred to as the “range-related cost”—as a measurement of range anxiety. The objective function is linked to policy-relevant parameters, including battery cost and price markup, battery utilization, charging infrastructure availability, vehicle efficiency, electricity and gasoline prices, household vehicle ownership, daily driving patterns, discount rate, and perceived vehicle lifetime. Qualitative discussion of the framework and its empirical application to a sample (N=36664) representing new car drivers in the United States is included. The quantitative results strongly suggest that ranges of less than 100 miles are likely to be more popular in the BEV market for a long period of time. The average optimal range among United States (U.S.) drivers is found to be largely inelastic. Still, battery cost reduction significantly drives BEV demand toward longer ranges, whereas improvement in the charging infrastructure is found to significantly drive BEV demand toward shorter ranges. The bias of a single-range assumption and the effects of range optimization and diversification in reducing such biases are both found to be significant.

[0009] J. Barco, A. Guerra, L. Muñoz, N. Quijano, "Optimal Routing and Scheduling of Charge for Electric Vehicles: A Case Study", Mathematical Problems in Engineering, vol. 2017, Article ID 8509783, 16 pages, 2017. There are increasing interests in improving public transportation systems. One of the proposed strategies for this improvement is the use of Battery Electric Vehicles (BEVs). This approach leads to a new challenge as the BEVs’ routing is exposed to the traditional routing problems of conventional vehicles, as well as the particular requirements of the electrical technologies of BEVs. Examples of BEVs’ routing problems include the autonomy, battery degradation, and charge process. This work presents a differential evolution algorithm for solving an electric vehicle routing problem (EVRP). The formulation of the EVRP to be solved is based on a scheme to coordinate the BEVs’ routing and recharge scheduling, considering operation and battery degradation costs. A model based on the longitudinal dynamics equation of motion estimates the energy consumption of each BEV. A case study, consisting of an airport shuttle service scenario, is used to illustrate the proposed methodology. For this transport service, the BEV energy consumption is estimated based on experimentally measured driving patterns.

[0010] Sundstr¨om, Olle and Carl Binding. “Optimization Methods to Plan the Charging of Electric Vehicle Fleets.” (2010). This paper describes an approach to optimize electric vehicle battery charging behavior with the goal of minimizing charging costs, achieving satisfactory state-of-energy levels, and optimal power balancing. Two methods for charging schedule optimization are compared. The first formulation uses a linear approximation of the battery behavior, whereas the second uses a quadratic approximation. A non-linear and state-dependent battery model is used to evaluate the solutions of the two methods. Our results indicate that the linear approximation is sufficient when considering the electric vehicle charging plan optimization.

[0011] Hence, it becomes imperative to create a method and system which solves allocation of loads in such way that EVs and Chargers can be effectively used without compromising the allocation of loads.

OBJECT(S) OF THE INVENTION

[0012] Primary object of the present invention is to overcome the drawback associated with the prior systems and methods.

[0013] Another object of the present invention is to provide a system and method for effective and efficient allocation and management of resources involved in the delivery of loads.

[0014] Yet another object of the present invention is to provide a system and method for delivery of loads by EVs.

[0015] Yet another object of the present invention is to provide a system and method that helps to determine the best EV, Rider and Charger to be utilized for a load delivery.

[0016] Yet another object of the present invention is to provide a system and method that allocates loads in such a manner that EVs and Chargers can be effectively used without compromising the allocation of loads.

[0017] Yet another object of the present invention is to provide a system and method that allocates load in such a manner that EVs never run out of battery charge.

[0018] Yet another object of the present invention is to provide a system and method that minimizes the total cost involved in the delivery of the loads.

[0019] Yet another object of the present invention is to provide a method and system for allocation of EVs, chargers and riders to a load delivery which is dynamic.

SUMMARY OF THE INVENTION

[0020] In an aspect of the invention, there is provided a method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising the steps of:
• Receiving information from EVs, Riders, Chargers and Shippers (101) in a database;
• For each information received from the Shippers (101), determining initial cost for each EV to complete the trip;
• For each EV, determining the cost to charge the vehicle at all available Chargers;
• For each rider, determining the cost to use each of the EVs;
• Comparing each cost and eliminating non-compatible options;
• Ranking each of the costs based on total cost of delivery;
• Determining that no EVs go out of charge post-delivery; and
• Allocating the EVs, Riders, Chargers and Shippers (101).

[0021] In an another aspect of the invention, there is provided a system for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising:
• Electric Vehicles (EVs) configured to deliver a package from one place to another, wherein EVs comprises a telematics device (112) configured to send information over network to cloud;
• Chargers configured to charge the EVs;
• Riders to drive the EVs for delivering the package from one place to another, wherein the Rider uses a Rider User Interface (110, 117) configured to enter and edit information;
• Shippers (101) intending to deliver the package from one place to another, wherein the Shippers (101) uses a Shipper User Interface (103) configured to enter and edit information;
• An Administrative Tool comprising of a Task Interface (115), an EV and Charger Interface (116) and a Rider Interface (117);
• An Allocation Tool configured to collect and perform action on the information received from EVs, Riders, Chargers and Shippers (101); and
• Database configured to store information received from EVs (113), Riders (111), Chargers (107), Shippers (101) and Allocation Data (108), wherein data stored in the database is updated on real-time basis.

BRIEF DESCRIPTION OF DRAWINGS

[0022] To clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings in which:

[0023] Figure 1: Illustrates an exemplary embodiment of the method steps in accordance with the present invention

[0024] Figure 2: Illustrates an exemplary embodiment of the system diagram of the high-level architecture of the system.

[0025] Figure 3: Illustrates an exemplary embodiment of the Bulk processes block diagram to show main processes.

[0026] Figure 4: Illustrates a flow chart explaining the different steps taken while assigning an EV to a task.

[0027] Figure 5: Illustrates an exemplary embodiment of the system in accordance with the present invention.
DETAILED DESCRIPTION OF THE INVENTION

[0028] The following detailed description is merely exemplary in nature and is not intended to limit the described embodiments or the application and uses of the described embodiments. As used herein, the word “exemplary” or “illustrative” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary or “illustrative” is not necessarily to be construed as preferred or advantageous over other implementations. All of the implementations described below are exemplary implementations provided to enable persons skilled in the art to make or use the embodiments of the disclosure and are not intended to limit the scope of the disclosure, which is defined by the claims. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. It is also to be understood that the specific devices and processes illustrated in the attached drawings, and described in the following specification, are simply exemplary embodiments of the inventive concepts defined in the appended claims. Hence, specific dimensions and other physical characteristics relating to the embodiments disclosed herein are not to be considered as limiting, unless the claims expressly state otherwise.

[0029] In an aspect of the invention, there is provided a method and system for allocation of Electric Vehicles (EVs), chargers and riders to logistic delivery.

[0030] In an embodiment of the present invention, an allocator can assign the loads, EVs and chargers dynamically based on the requirement in such a way so that EVs never run out of battery charge.

[0031] In an another embodiment of the present invention, the allocator will gather information about EVs, loads, chargers and riders, then feed it to a series of business rules to eliminate options which are not possible and finally optimizing the result for minimizing the total cost for the allocation.

[0032] In an exemplary embodiment of the present invention, at a central system/allocator information is received from the EVs, riders, charges and loads. For each load, initial cost for each EV to complete a trip is determined. The cost to charge the EV is determined at all the chargers available for each EV. The cost involved for each rider to use each of the EVs is determined.

[0033] In another preferred embodiment of the present invention, cost determined for loads, EVs and riders are compared with business logic. Based on the comparison results, non-compatible options are eliminated.

[0034] In an embodiment of the present invention, each cost involved are ranked on the basis of the total cost of delivery. Series of business logic are applied to determine that no EVs go out of charge post delivery of the load.

[0035] In an embodiment of the present invention, EVs, riders, loads and chargers are effectively and efficiently allocated.

[0036] In an embodiment, the words ‘loads’, ‘package’, ‘packet’, task etc. are interchangeably used and will mean one thing or another for the subject application.

[0037] In an another preferred embodiment of the present invention, a method and system for allocating loads, such as parcel boxes, to EVs and to EV chargers is disclosed. The method comprises allocating parcel box to EVs by evaluating each parcel boxes distance, travel time and charge required for each of the EV and further allocating each EV to a rider and a charger without EV running out of charge. Evaluation is based on a series of methods and business logic which helps to determine the best EV, rider and charger to be utilized for a load delivery.

[0038] In an embodiment, some of the use cases of the present invention includes allocation of loads to EVs in an on-demand parcel, allocation of passengers to EVs in a ride hailing service and allocation of riders to the EVs in an EV sharing models.

[0039] In an another embodiment, the method includes allocation of electric vehicles to different tasks based on telemetry data from electric vehicles and chargers.

[0040] In an embodiment, allocation of chargers and electric vehicle are done using telemetry-based data. There can be other claims which can be defined based on the uses of telemetry in allocation of electric vehicle to different task based on load and rider availability.

[0041] In an embodiment of the present invention, there is provided a method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising the steps of:
• Receiving information from EVs, Riders, Chargers and Shippers (101) in a database;
• For each information received from the Shippers (101), determining initial cost for each EV to complete the trip;
• For each EV, determining the cost to charge the vehicle at all available Chargers;
• For each rider, determining the cost to use each of the EVs;
• Comparing each cost and eliminating non-compatible options;
• Ranking each of the costs based on total cost of delivery;
• Determining that no EVs go out of charge post-delivery; and
• Allocating the EVs, Riders, Chargers and Shippers (101).

[0042] In an embodiment, there is provided a system for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising:

• Electric Vehicles (EVs) configured to deliver a package from one place to another, wherein EVs comprises a telematics device (112) configured to send information over network to cloud;
• Chargers configured to charge the EVs;
• Riders to drive the EVs for delivering the package from one place to another, wherein the Rider uses a Rider User Interface (110, 117) configured to enter and edit information;
• Shippers (101) intending to deliver the package from one place to another, wherein the Shippers (101) uses a Shipper User Interface (103) configured to enter and edit information;
• An Administrative Tool comprising of a Task Interface (115), an EV and Charger Interface (116) and a Rider Interface (117);
• An Allocation Tool configured to collect and perform action on the information received from EVs, Riders, Chargers and Shippers (101); and
• Database configured to store information received from EVs (113), Riders (111), Chargers (107), Shippers (101) and Allocation data (108), wherein data stored in the database is updated on real-time basis.

[0043] In an embodiment, wherein the information received from EVs comprises real time location and state of charge of the vehicle, wherein a telematics device (112) is connected to the main communication bus of the EVs and comprises a sim card configured to send information over network to cloud.

[0044] In an another preferred embodiment of the present invention, the information received from Chargers comprises static information about Charger properties such as location, capacity and Charger type.

[0045] In an embodiment, the Charger properties are updated automatically whenever a new charger is added and further availability of Chargers changes to ‘not available’ whenever the Charger is connected to an EV.

[0046] In an embodiment, the information received from Riders comprises the availability of the Rider for a certain time in a day, wherein the information is entered and editable via a Rider User Interface (110, 117).

[0047] In an another embodiment of the present invention, the information received from Shippers (101) contains a task comprising package type, electric vehicle type needed, weight of the package, pickup location and drop location, wherein the information is entered and editable via a Shipper User Interface (103).

[0048] In an embodiment of the present invention, the allocation of the EVs, Riders, Chargers and Shippers (101) comprises the steps of:
a) Receiving information from the Shipper (101) related to the task;
b) Matching of EVs on the basis of the task received from the Shipper (101), wherein the EVs are categorized on the basis of form;
c) Selection of EVs either on the basis of aerial distance or road distance, wherein distance is calculated between location of EV and pickup location of the package;
d) Sorting the EVs in ascending order to complete the task received from the Shipper (101);
e) Selection of the EV with least required state of charge;
f) Checking the availability of the Riders, wherein the current stage of charge is updated to complete the task received from the Shipper (101) if Rider is not available; and
g) Allocation of said EV to the Rider.

[0049] In an embodiment of the present invention, selection of the EV is based on factors comprising:
a. Availability of Chargers in the predefined radius of drop location, wherein predefined radius is configurable and increases if Chargers are not available in the drop location; and

b. Ability of the EV to reach the Chargers with the current state of charge, wherein the current state of charge is updated for the EV to complete the task received from the Shipper (101).

[0050] In an embodiment, the form of EVs is selected from a group comprising of two-wheelers, three-wheelers and four-wheelers.

[0051] In an another embodiment of the present invention, Receiving Information from Electric Vehicles includes:
• Electric vehicles get fitted with telematics device which sends out real time location of the vehicle and state of charge to the cloud and saves in a database.
o Telematics device is connected to the main communication bus of the vehicle. Which reads and stores vehicle data.
o Telematics device has a sim card to send data over network to cloud.
• Inside database electric vehicles are categorised as form factor (Two-Wheeler, Three-Wheeler, etc)
• For each vehicle the latest location with vehicle’s state of charge gets updated at an interval.
• New EV gets added via admin portal to keep all vehicles at one place.

[0052] In an embodiment, Receiving Information about available Chargers includes:
• Static information about charger properties such as location, capacity, charger type is saved in database which gets updated whenever a new charger gets added.
• Availability of charger changes status to not available whenever the charger connects to a vehicle.

[0053] In an another embodiment of the present invention, Receiving Information from Riders includes:
• Riders are available for a certain time in a day.
• Their availability is saved in a database.
• Rider’s availability information can be edited from Rider interface.

[0054] In an embodiment, Receiving Task from Shipper includes:
• Shippers are users who needs to send a package from location A to location B with Electric Vehicle.
• They use an interface to record the task details.
• These task details mainly consist of package type, electric vehicle type needed, weight of the package, pickup location and drop location.

[0055] In an another embodiment of the present invention, Fig 1 illustrates system diagram of the high-level architecture of the system.
• 101 User who wish to ship any package or load with Electric vehicle is shipper.
• 103 Task interface is the interface shipper uses to submit task. It can be either mobile or web interface.
• 104 Allocation tool which captures task details and does action on tasks data
• 105 Allocation tool which captures the details and does action on electric vehicle and chargers’ data
• 106 Allocation tool which captures the details and does action on rider or driver who drives the electric vehicle data
• 107 Database consisting latest charger information received
• 108 Database consisting allocation information about electric vehicles and tasks which helps determining free vehicles.
• 109 Riders or drivers can make themselves available for a window. This help in rostering of drivers in the system and profile of the rider is maintained and editable by the rider via User Interface.
• 110 Riders or drivers use interface to make themselves available
• 111 Database consisting rider or driver of electric vehicle information.
• 112 Telematics device which sends electric vehicle data to cloud
• 113 Database consisting electric vehicle data which is received by telematics
• 114 Database consisting task details from user or shipper.
• 115 Task interface of the Administrative Tool to manage the information related to task or add task related information. This also helps in managing the Shippers and task related to information by the administrator.
• 116 EV and Charger Interface of the Administrative Tool to add and delete new EVs and Chargers to the database. This also helps in managing the EVs and Chargers by the administrator.
• 117 Rider/Driver Interface of the Administrative Tool to add and delete new Rider/Driver. This also helps in managing the Rider/Driver by the administrator.

[0056] In an another embodiment, profile of each and every EV, Chargers, Riders and Shippers are created and maintained separately.
[0057] In an embodiment, Fig. 2 illustrates a Bulk processes block diagram to show main processes.
• 201 The block shows process of receiving task from shipper or user
• 202 The block shows validating the task for information and matching with right type of electric vehicle.
• 203 The block shows the process of storing the task in database
• 204 The block shows the process of allocating electric vehicles to different tasks based on business logic and rules.
• 205 The block shows the process of handling different exception generated while allocating the electric vehicle to tasks
• 206 The block shows the process of reallocating different EVs to different chargers after allocating EVs to the tasks

[0058] In an another preferred embodiment of the present invention, Fig 3 illustrates a Flow chart explaining the different steps taken while assigning an EV to a task.
• 301 Checking if system has received any new tasks from user or shipper
• 302 Matching of electric vehicle form factor based on user or shipper preference.
• 303 Select electric vehicles with predefined aerial distance from pickup location.
• 304 Select electric vehicles with predefined road distance from pickup location.
• 305 Sort the table or list consisting electric vehicle with least required state of charge to complete the task at first.
• 306 selections of first electric vehicle on the list or table.
• 307 Check if compatible and available charger is present within a radius of predefined distance from the drop location.
• 308 If the answer to the check is no then increase the predefined radius by a predefined distance.
• 309 If the answer for 307 is yes then check if electric vehicle can reach to the charging station with the current state of charge in the vehicle.
• 310 If the answer is no to 309 then initiate a process to add extra charge required to reach to the charging station near drop location and update the required state of charge for the electric vehicle to complete the task.
• 311 If the answer to 309 is yes then check if rider or driver is available for the time required to complete the task.
• 312 If the answer to 311 is no then initiate a process to add extra charge required to complete the task.
• 313 If the answer to 311 is yes then allocate the said electric vehicle to the task.

[0059] In an embodiment, Computer system 400 can include a display interface 401 that forwards graphics, text, and other data from the communication infrastructure 402 (or from a frame buffer not shown) for display on the display unit 405. Computer system 400 also includes a main memory 403, preferably random access memory (RAM), and may also include a secondary memory 413. The secondary memory 413 may include, for example, a hard disk drive 406 and/or a removable storage drive 407, representing a floppy disk drive, a magnetic tape drive, an optical disk drive, etc. The removable storage drive 407 reads from and/or writes to a removable storage unit 410 in a well-known manner. The removable storage unit 410 represents a floppy disk, magnetic tape, optical disk, etc. which is read by and written to by removable storage drive 407. As will be appreciated, the removable storage unit 410 includes a computer-usable storage medium having stored therein computer software and/or data. In alternative embodiments, secondary memory 413 may include other similar devices for allowing computer programs or other instructions to be loaded into computer system 400. Such devices may include, for example, a removable storage unit 411 and an interface 408. Examples of such may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an erasable programmable read-only memory (EPROM), or programmable read-only memory (PROM)) and associated socket, and other removable storage units 411 and interfaces 408, which allow software and data to be transferred from the removable storage unit 411 to computer system 400. Computer system 400 may also include a communications interface 409. Communications interface 409 allows software and data to be transferred between computer system 400 and external devices. Examples of communications interface 409 may include a modem, a network interface (such as an Ethernet card), a communications port, a Personal Computer Memory Card International Association (PCMCIA) slot and card, etc. Software and data transferred via communications interface 409 are in the form of signals 628 which may be electronic, electromagnetic, optical or other signals capable of being received by communications interface 409. These signals 414 are provided to communications interface 409 via a communications path (e.g., channel) 412. This channel 412 carries signals 414 and may be implemented using wire or cable, fibre optics, a telephone line, a cellular link, a radio frequency (RF) link and other communications channels. In this document, the terms "computer program medium’ and “computer usable medium' are used to generally refer to media Such as removable storage drive 407, a hard disk installed in hard disk drive 406, and signals 414. These computer program products provide software to computer system 400. The invention is directed to such computer program products. Computer programs (also referred to as computer control logic) are stored in main memory 403 and/or secondary memory 413. Computer programs may also be received via communications interface 409. Such computer programs, when executed, enable the computer system 400 to perform the features of the present invention, as discussed herein. In particular, the computer programs, when executed, enable the processor 402 to perform the features of the present invention. Accordingly, such computer programs represent controllers of the computer system 400. In an embodiment where the invention is implemented using software, the Software may be stored in a computer program product and loaded into computer system 400 using removable storage drive 407, hard drive 406 or communications interface 409. The control logic (software), when executed by processor 402, causes the processor 402 to perform the functions of the invention as described herein. In another embodiment, the invention is implemented primarily in hardware using, for example, hardware components Such as application-specific integrated circuits (ASICs). Implementation of the hardware state machine so as to perform the functions described herein will be apparent to persons skilled in the relevant art(s). In yet another embodiment, the invention is implemented using a combination of both hardware and software.

[0060] In an embodiment of the present invention, the allocator can assign the loads, EVs and chargers dynamically based on the requirement in such a way so that EVs never run out of battery charge.

[0061] Some of the examples of use-cases may include:
1. Allocation of loads to EVs in an on-demand parcel
2. Allocation of passengers to EVs in a ride-hailing service
3. Allocation of riders to the EVs in EV sharing models

[0062] In an another embodiment, the allocator will gather information about EVs, loads, chargers and riders, then feed it to a series of business rules to eliminate options that are not possible. Finally optimizing the result for minimising the total cost for the allocation.

[0063] The present invention as described above, it is to be understood that this invention is not limited to particular methodologies and materials described, as these may vary as per the person skilled in the art. It is also to be understood that the terminology used in the description is for the purpose of describing the particular embodiments only, and is not intended to limit the scope of the present invention.

[0064] It can be appreciated that the aforesaid embodiments are only exemplary embodiments adopted to describe the principles of the present invention, and the present invention is not merely limited thereto. Various variants and modifications may be made by those of ordinary skill in the art without departing from the essence of the present invention, and these variants and modifications are also covered within the scope of the present invention. Accordingly, although the invention has been described with reference to specific examples, it can be appreciated by those skilled in the art that the invention can be embodied in many other forms. It can also be appreciated by those skilled in the art that the features of the various examples described can be combined in other combinations.

CLAIMS:We Claim:
1. A method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising the steps of:
a. Receiving information from EVs, Riders, Chargers and Shippers (101) in a database;
b. For each information received from the Shippers (101), determining initial cost for each EV to complete the trip;
c. For each EV, determining the cost to charge the vehicle at all available Chargers;
d. For each rider, determining the cost to use each of the EVs;
e. Comparing each cost and eliminating non-compatible options;
f. Ranking each of the costs based on total cost of delivery;
g. Determining that no EVs go out of charge post-delivery; and
h. Allocating the EVs, Riders, Chargers and Shippers (101).

2. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 1, wherein the information received from EVs comprises real time location and state of charge of the vehicle,
wherein a telematics device (112) is connected to the main communication bus of the EVs and comprises a sim card configured to send information over network to cloud.

3. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 1, wherein the information received from Chargers comprises static information about Charger properties such as location, capacity and Charger type.

4. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 3, wherein the Charger properties are updated automatically whenever a new charger is added and further availability of Chargers changes to ‘not available’ whenever the Charger is connected to an EV.

5. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 1, wherein the information received from Riders comprises the availability of the Rider for a certain time in a day, wherein the information is entered and editable via a Rider User Interface (110).

6. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 1, wherein the information received from Shippers (101) contains a task comprising package type, electric vehicle type needed, weight of the package, pickup location and drop location, wherein the information is entered and editable via a Shipper User Interface (103).

7. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 1, wherein the allocation of the EVs, Riders, Chargers and Shippers (101) comprises the steps of:
a) Receiving information from the Shipper (101) related to the task;
b) Matching of EVs on the basis of the task received from the Shipper (101), wherein the EVs are categorized on the basis of form;
c) Selection of EVs either on the basis of aerial distance or road distance, wherein distance is calculated between location of EV and pickup location of the package;
d) Sorting the EVs in ascending order to complete the task received from the Shipper (101);
e) Selection of the EV with least required state of charge;
f) Checking the availability of the Riders, wherein the current stage of charge is updated to complete the task received from the Shipper (101) if Rider is not available; and
g) Allocation of said EV to the Rider.

8. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 7, wherein selection of the EV is based on factors comprising:

a. Availability of Chargers in the predefined radius of drop location, wherein predefined radius is configurable and increases if Chargers are not available in the drop location; and

b. Ability of the EV to reach the Chargers with the current state of charge, wherein the current state of charge is updated for the EV to complete the task received from the Shipper (101).

9. The method for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery as claimed in Claim 7, wherein the form of EVs is selected from a group comprising of two-wheelers, three-wheelers and four-wheelers.

10. A system for allocation of Electric Vehicles (EVs), Chargers and Riders to logistic delivery comprising:

a. Electric Vehicles (EVs) configured to deliver a package from one place to another, wherein EVs comprises a telematics device (112) configured to send information over network to cloud;
b. Chargers configured to charge the EVs;
c. Riders to drive the EVs for delivering the package from one place to another, wherein the Rider uses a Rider User Interface (110) configured to enter and edit information;
d. Shippers (101) intending to deliver the package from one place to another, wherein the Shippers (101) uses a Shipper User Interface (103) configured to enter and edit information;
e. An Administrative Tool comprising of a Task Interface (115), an EV and Charger Interface (116) and a Rider Interface (117);
f. An Allocation Tool configured to collect and perform action on the information received from EVs, Riders, Chargers and Shippers (101); and
g. Database configured to store information received from EVs (113), Riders (111), Chargers (107), Shippers (101) and Allocation Data (108), wherein data stored in the database is updated on real-time basis.