Optimized charging of energy storage devices

Abstract

Example approaches for optimizing the charging process of an energy storage devices, are described. In an example, initially, a plurality of charging attributes, including an initial state of charge (SoC), temperature, and user-defined charging time, of the energy storage device is obtained. Thereafter, charging characteristics of the energy storage device are extracted from a data repository. Then, an SoC function indicating a linear relationship between attainable SoC, SoC rise per minute, and individual charging time for various charging rates is generated. The SoC function is then optimized against multiple charging constraints to determine a charging profile that maximizes the SoC within the user-specified time while maintaining safety limits. The charging profile is used to control the charging current provided by a power supply source to the energy storage device, resulting in an efficient and flexible charging process tailored to user preferences and device conditions.

Description

OPTIMIZED CHARGING OF ENERGY STORAGE DEVICESBACKGROUND

[0001] Energy storage devices, such as batteries are main source of power in electric vehicles (EVs). The batteries used in the EVs are typically rechargeable and once discharged, the batteries are required to be connected to a power supply source for recharging the same up to a certain level. The power supply source may range from standard household outlets to dedicated fast-charging stations. The fast-charging stations may allow drivers to quickly recharge the batteries and continue journeys with less downtime.BRIEF DESCRIPTION OF DRAWINGS

[0002] The detailed description is provided with reference to the accompanying figures, wherein:

[0003] FIG. 1 illustrates an exemplary charging environment of an electric vehicle, in accordance with one implementation of the present subject matter;

[0004] FIG. 2 illustrates a block diagram of a control unit of an electric vehicle, in accordance with one implementation of the present subject matter; and

[0005] FIG. 3 illustrates an exemplary method for charging an energy storage device based on a charging profile, in accordance with one implementation of the present subject matter.

[0006] Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements. The figures are not necessarily to scale, and the size of some parts may be exaggerated to more clearly illustrate the example shown. Moreover, the drawings provide examples and / or implementations consistent with the description; however, the description is not limited to the examples and / or implementations provided in the drawings.DETAILED DESCRIPTION

[0007] Generally, fast-charging techniques are implemented for charging energy storage devices of EVs in a short period of time, without much downtime of the EV. However, the fast-charging techniques often come with a trade-off between rapid charging times and the high charging rates (C-rates). High C-rates may cause the energy storage device to heat up excessively during the charging process, which not only increases the risk of overheating but may also lead to potential safety hazards, such as the explosion of the energy storage device. Additionally, the use of high C- rates for fast charging is known to reduce cycle life of the energy storage device, thereby compromising health and longevity of the energy storage device. Such fast-charging techniques may necessitate frequent replacements of the energy storage device, thereby increasing cost of EV.

[0008] Moreover, existing fast-charging techniques do not consider varying preferences and requirements of users, who may charge the EVs for durations that differ from a manufacturer's specified values of state of charge (SOC) or voltage levels for the energy storage device. This may result in charging the energy storage device beyond a recommended upper temperature threshold, thus leading to inefficient operation and accelerated degradation of the energy storage device.

[0009] Furthermore, existing fast-charging techniques that provide linear or constant C-rates within a manufacturer's specified operational range do not offer the flexibility that users may require. This may lead to derations in the energy storage devices, where the energy storage device is operated below its maximum capability. Such derations, while intended to be protective, ultimately result in longer charging times compared to scenarios where the EV could be charged at its maximum capability.

[0010] Approaches for optimizing the charging process of energy storage devices based on user-defined parameters and device characteristics, are described. The approaches of the present subjectmatter provide adaptable and user-centric approach to EV battery charging that does not compromise the battery's performance or the user's convenience.

[0011] In a charging process, when the energy storage device is plugged in or connected with a power supply source for charging, the electric vehicle may obtain a plurality of charging attributes of the energy storage device, from the energy storage device as well as from a user. In an example, the plurality of charging attributes includes an initial or starting state of charge (SoC) of the energy storage device, an initial temperature of the energy storage device which indicates an SoC value and a temperature value at an instant when the energy storage device is just connected for charging, and an input time duration provided by the user when the energy storage device is connected for charging. Once the charging attributes are obtained, charging characteristics of the energy storage device may be extracted from a data repository. The data repository may be present in the EV or at a charging station. In an example, the charging characteristics may include change in SoC per minute and change in temperature per minute corresponding to a plurality of charging rates for the energy storage device.

[0012] Thereafter, the control unit of the electric vehicle may generate a state of charge (SoC) function corresponding to a charging operation. In an example, the SoC function may indicate a linear relation between an attainable SoC of the energy storage device with a SoC rise per minute corresponding to the plurality of charging rates and an individual charging time. Once generated, the electric vehicle may optimize the SoC function, against a plurality of charging constraints, to determine a charging profile of the EV. The charging constraints can be for example, a maximum allowable temperature, a maximum allowable voltage, or a maximum allowable current. While optimizing the SoC function, the control unit of the electric vehicle may incorporate the plurality of charging attributes and the charging characteristics of the energy storage device as limiting values within the charging constraints to maximize the SoC function. By maximizing thecharging function, a charging profile may be determined with respect to the input time provided by the user.

[0013] The charging profile may then be transmitted to the power supply source to be used as a standard profile based on which a charging current may be provided to the energy storage device for charging. The approach of the present subject matter allows for a more efficient and flexible charging process that can adapt to the specific requirements and conditions of the energy storage device and the user's preferences.

[0014] The following description sets forth exemplary aspects of the present disclosure. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure. Rather, the description also encompasses combinations and modifications to those exemplary aspects described herein.

[0015] FIG. 1 depicts an exemplary charging environment 100 within a schematic representation, according to an example. The charging environment 100 comprises an electric vehicle 102 connected to a power supply source 104 for charging an energy storage device 106 of the electric vehicle 102. Examples of such electric vehicle 102 may include, but are not limited to, an electric two-wheeler, an electric car, and an electric bus. The power supply source 104 may be any suitable source of electrical energy, such as a wall outlet, a dedicated charging station, or a renewable energy source. In some cases, the power supply source 104 may be part of a charging infrastructure that includes different types of charging stations, such as Level 1 , Level 2, or DC fast charging stations.

[0016] The connection between the electric vehicle 102 and the power supply source 104 (interchangeably used as power source 104) is represented by a solid line, indicating the physical connection through which electrical energy is transferred. Examples of the power source 104 may include a battery or a fuel cell among others. This connection may be established using a variety of methods and components, such as cables, connectors, or wireless charging technologies, depending on the specificdesign and requirements of the electric vehicle 102 and the power source 104.

[0017] In one example, the electric vehicle 102 may be connected to the power supply source 104 using different types of connectors or adapters, depending on a specific design and requirements of the electric vehicle 102 and the power supply source 104. The connection may be established using advanced technologies such as inductive charging or wireless power transfer, which could provide a more convenient and efficient charging process.

[0018] In one example, the power supply source 104 may be a renewable energy source, such as a solar panel or a wind turbine. This may provide a more sustainable and environmentally friendly charging process. The power supply source 104 may also be part of a smart grid infrastructure, which could provide dynamic charging rates based on a current demand and supply of electricity.

[0019] In an example, the energy storage device 106 may be used to power different components of the electric vehicle 102. Further, although, the description is provided with respect to the electric vehicle 102 including the energy storage device 106, the description of the present subject matter may also be implemented for any electronic device comprising the energy storage device 106 without deviating from the scope of the present subject matter.

[0020] The electric vehicle 102 may further include a control unit 108 coupled to the energy storage device 106. The control unit 108 may be implemented using various types of processors or microcontrollers and may also include additional sensors, for example, a temperature sensor, a current sensor, and an energy storage device safety sensor, among others, for monitoring the state of the energy storage device 106 and the charging process. In one example, the control unit 108 may be implemented using different types of processors or microcontrollers, such as ARM processors, x86 processors, or custom-designed application-specific integrated circuits(ASICs). The control unit 108 may also be implemented using a combination of hardware and software components and could be integrated with other systems in the electric vehicle 102, such as the vehicle's navigation system or the vehicle's energy management system.

[0021] The control unit 108 may be responsible for managing the charging process, including the generation of the charging profile as described in the present disclosure.

[0022] The control unit 108 may be configured to obtain information, such as a current state of charge (SoC) and a current temperature of the energy storage device 106 which indicates the SoC value and the temperature value when the energy storage device 106 is connected to the power source 104 for charging over a period of time. This information may be used by the control unit 108 to monitor the progress of the charging process. Further details regarding the aspects of generation and optimization of the SoC function are provided below with respect to Figure 2.

[0023] In one aspect, the control unit 108 may determine the charging profile based on the current SoC and the current temperature. In an example, the charging profile be generated through a charging signal. Thereafter the charging profile can be transmitted to the power source 104 connected to the energy storage device 106 for charging the electric vehicle 202. The charging signal may include information about the preferred charging parameters, such as a charging current, a charging voltage, or a charging time of the energy storage device 106. In response to receiving the charging signal, the power source 104 may provide the charging current to the energy storage device 106 based on the charging profile represented in the charging signal.

[0024] Further, in an example, the charging signal generated by the control unit 204 could include additional information about desired charging parameters, such as a charging power, a charging efficiency, or a charging mode (e.g., fast charging, slow charging, or trickle charging). The chargingsignal could also include error correction codes or encryption to ensure the integrity and security of the charging process.

[0025] The controlled stepping up of the SoC helps in avoiding accelerated degradation of the energy storage device 106 while also providing an optimized charging process within a customized charging duration.

[0026] FIG. 2 illustrates a block diagram 200 of an electric vehicle 202, according to an implementation of the present subject matter. In an example, the electric vehicle 202 is similar to the electric vehicle 102. The electric vehicle 102 includes a control unit 204 which is similar to the control unit 108. In addition, the electric vehicle 202 includes an energy storage device 206 and a power supply source 208, which are similar to the energy storage device 106 and the power supply source 104, respectively.

[0027] In one aspect, the energy storage device 206 may be a rechargeable battery, such as a lithium-ion battery, a nickel-metal hydride battery, a lead-acid battery, or a solid-state battery, etc. Each of these battery types may have different charging characteristics and may require different charging profiles. The energy storage device 206 may include indicators for indicating a current state of charge (SoC) and a current temperature. In an example, the indicators may be visual indicators to show operating condition of the energy storage device 206. The current SoC and the current temperature of the energy storage device 206 may be obtained when the energy storage device 206 is connected to the power supply source 208 for charging. The information pertaining to the current SoC and the current temperature may be used to monitor the progress of the charging process.

[0028] Further, the electric vehicle 202 may include a human machine interface (HMI) 212. The HMI 212 is shown with an input window 214 for receiving an input. For example, a user can specify a desired charging duration through the input window 214. In some cases, the HMI 212 may be implemented using different types of interfaces, such as a touchscreeninterface, a voice-controlled interface, or a physical button or dial etc. The HMI 212 could also provide feedback to the user about the charging process, such as an estimated remaining time or the current SoC.

[0029] In an implementation, the EV 202 may be coupled to a data repository 216. The data repository 216 may be implemented using different types of storage devices, such as a hard disk drive, a solid-state drive, or a cloud-based storage service. The data repository 216 may be a single repository, or multiple other sources either external or internally present within the electric vehicle without deviating from the scope of the present subject matter. In such cases, each of such multiple repositories may be interconnected through a network (not shown in FIG. 2). The network may be a private network or a public network and may be implemented as a wired network, a wireless network, or a combination of a wired and wireless network. The network may also include a collection of individual networks, interconnected with each other and functioning as a single large network. Examples of such individual networks include, but are not limited to, Global System for Mobile Communication (GSM) network, Universal Mobile Telecommunications System (UMTS) network, Personal Communications Service (PCS) network, Time Division Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network, Next Generation Network (NGN), Public Switched Telephone Network (PSTN), Long Term Evolution (LTE), and Integrated Services Digital network (ISDN).

[0030] The data repository 216 may store various charging characteristics associated with the EV 202. The charging characteristics may be used to determine the charging profile of the energy storage device 206. The charging characteristics may include change in SoC per minute and change in temperature per minute corresponding to the plurality of charging rates for the energy storage device 206. These characteristics are stored in the data repository 216 based on previously conducted charging operations on the energy storage device 206. The data repository 216 mayalso include different types of data, such as historical charging data, manufacturer-provided charging data, or user-provided charging data.

[0031] The control unit 204 may further include a processor 218 and interface(s) 220, as well as memory(s) 222, and data 224. The control unit 204 may also include additional sensors for monitoring the current SoC of the energy storage device 206 and the charging process.

[0032] In another example, the control unit 204 may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, or in combination thereof. For a firmware and / or software implementation, the methodologies may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein.

[0033] The interface(s) 220 may allow a connection or coupling of the control unit 204 with one or more of the energy storage devices 206, the power supply source 208, the HMI 212, and the data repository 216 through a wired (e.g., Local Area Network (LAN)) connection or through a wireless connection (e.g., Bluetooth®, Wi-Fi). The interface(s) 220 may also enable intercommunication between different logical as well as hardware components of the control unit 204.

[0034] The processor 218 may be implemented as one or more of a microprocessor(s), a microcomputer(s), a microcontroller(s), a digital signal processor(s), a central processing unit(s), a state machine(s), a logic circuitry(s), and / or other device(s) that manipulate signals based on operational instructions. The memory(s) 222 may be a computer-readable medium, examples of which include volatile memory (e.g., RAM), and / or non-volatile memory (e.g., Erasable Programmable read-only memory, i.e., EPROM, flash memory, etc.). The memory(s) 222 may be an externalmemory or internal memory, such as a flash drive, a compact disk drive, an external hard disk drive, or the like. The memory(s) 222 may further include data which either may be utilized or generated during operation of the control unit 204.

[0035] The data 224, on the other hand, includes data that is either stored or generated as a result of functions implemented by the control unit 204. It may be further noted that information stored and available in the data 224 may be utilized by the control unit 204 for performing various functions by the EV 202. In an example, the data 224 may include current SoC 226, current temperature 228, target SoC 230, charging characteristics 232, charging profile 234, and other data 236. Further, the other data 236, amongst other things, may serve as a repository for storing data that is processed, or received, or generated as a result of execution of instructions comprised in the control unit 204.

[0036] In an example, the current SoC 226 and the current temperature 228 may represent SoC and temperature, respectively, of the energy storage device 206 and may be obtained from the energy storage device 206. For example, there are plurality of sensors installed or attached in the vicinity of the energy storage device 206 which monitor several attributes, such as the SoC and temperature, of the energy storage device 206, to be provided to the control unit 204. Further, the target SoC 230 may be understood as the SoC up to which the charging of the energy storage device 206 is desired to be performed. In one example, the target SoC 230 is entered by a user on the HMI 212 or it may be a default preset value, e.g., 100% SoC.

[0037] As has been described above, the charging characteristic(s) 232 may include change in SoC per minute and change in temperature per minute corresponding to a plurality of charging rates (or c-rates) for the plurality of energy storage device 206. Such charging characteristics are recorded or maintained by various manufacturers or suppliers, or industry experts based on previous charging operation of the similar type of theenergy storage device 206. For example, the energy storage device 206, when charged in the past, would have experienced changes in SoC per minute and changes in temperature per minute. The same data is recorded and stored in the data repository 216. Such data is updated continuously based on charging operations performed on various energy storage devices 206.

[0038] The charging profile 234 may be used to manage the charging process based on the user's input and the energy storage device's characteristics. However, other implementations of the control unit 204 may also be possible, without deviating from the scope of the present subject matter.

[0039] As is depicted in FIG.2, the power supply source 208 is connected to the control unit 204 via solid lines, indicating a physical or electrical connection. The power supply source 208 may be any suitable source of electrical energy, such as a wall outlet, a dedicated charging station, or a renewable energy source. In some cases, the power supply source 208 may be part of a charging infrastructure that includes different types of charging stations, such as Level 1 , Level 2, or DC fast charging stations. The charging profile may be adjusted based on the type of charging station to optimize the charging process.

[0040] In operation, the control unit 204 may obtain a plurality of charging attributes of the energy storage device 206. These charging attributes include a starting state of charge (SoC), a starting temperature of the energy storage device 206 which indicates an SoC value and a temperature value at an instant when the energy storage device is just connected for charging, and an input time provided by a user when the energy storage device 206 is connected for charging. In an example, the input time is provided by the user via the HMI 212 installed on the electric vehicle 202 and it indicates the time for which the user wants to charge the energy storage device 206. The control unit 204 may also extract thecharging characteristics of the energy storage device 206 from the data repository 216.

[0041] For extracting the charging characteristics of the energy storage device 206, the control unit 208 may determine a plurality of device attributes of the energy storage device 206, which include charging capacity and chemical formulation of the energy storage device 206. The control unit 208 may then select charging characteristics of the energy storage device 206 from the data repository based on the plurality of device attributes. The data repository 212 is connected to the control unit 204 via a solid line, indicating a physical or electrical connection. The data repository 212 may store charging characteristics of a plurality of energy storage devices 206 segregated based on device attributes.

[0042] In an example, the charging characteristics include change in SoC per minute and change in temperature per minute corresponding to the plurality of charging rates for the energy storage device 206.

[0043] Based on the plurality of charging attributes and the charging characteristics, the control unit 204 may generate an SoC function indicating a linear relation between an attainable SoC of the energy storage device 206 with a SoC rise per minute corresponding to the plurality of charging rates and an individual charging time corresponding to the plurality of charging rates.

[0044] The control unit 204 may optimize the SoC function against a plurality of charging constraints. In an example, while optimizing the SoC function, the plurality of charging constraints incorporates the plurality of charging attributes and the charging characteristics . Upon optimization of the SoC function, the control unit 204 may generate a charging profile. The charging profile includes a value of a charging parameter. Examples of charging attributes include, but are note limited to, a charging voltage, a charging temperature, a charging current, a charging time, or combination thereof.

[0045] In an example, the current SoC 226 and the current temperature 228 of the energy storage device 206 may be obtained over a period of time when the energy storage device 206 has been connected to the power supply source 208 for charging. The input time may be provided by the user via the HMI 212 installed on the electric vehicle 202.

[0046] In an example, the SoC function as described above is a linear equation which may be optimized (i.e., maximized) using linear programming techniques with respect to certain constraints. There are a number of techniques available to optimize such equations. In an example, to optimize the SoC function, the control unit 204 may maximize the SoC function with respect to the plurality of charging constraints using a dual simplex method so as to determine a maximum attainable SoC within the input time.

[0047] In an example, the SoC function can be mathematically defined as follows: attainable SoC = (SoC rise per min)i * ts, herein ‘i’ varies from 1 to 9 and each£ts’ correspond to one of the plurality of charging rates.The plurality of charging constraints are applied as per the below equations:AJemp <= tempjimit - start temperature;Total charging time <= input time;A_SoC >= min((temp_limit - start temperature)*f, X3 - Start SoC);A_SoC X1 >= max(min(X1 , X3) - max(start SoC, X2), 0);A_SoC X2 <= max(min(X2, X3) - start SoC, 0); and tempjimit - start temperature;

[0048] In an example, the temp imit is the maximum allowable temperature of the energy storage device 206 for charging, start temperature is the temperature of energy storage device 206 at the start of the charging session, input time is the time selected by the user for performing charging, start SoC is the SoC at the start of the charging session, ‘f’ is the factor based on the ratio of temperature change per minuteto the SoC change per minute of the lowest charging rate, ‘XT is the SoC above which certain charging rates are not allowed due to voltage buildup constraints, X2’ is the SoC below which only certain C rates are allowed, ‘X3’ is the maximum allowable SoC limit for charging, total charging time is sum of charging times for each of the c-rates possible, A_temp is the increase in temperature of a pack of the energy storage device 206 during a proposed charging cycle. In one example, as per industry standards, the temperature of the energy storage device 206 should not increase beyond 45 °C (i.e. , the temp imit is 45 °C) while charging, however, it may take any possible value based on the requirement.

[0049] It may be noted that, the above-described constraints are derived or formulated to achieve best charging performance by keeping various parameters and attributes of the energy storage device 206 within limit. Examples of such limiting criteria include, but are not limited to, temperature and charging rates. Particularly, as per the limiting criteria, the temperature of the energy storage device 206 should not increase beyond the threshold value, fast charging should be achieved, and most effective charging rates should be selected, etc.

[0050] In an example, a comprehensive field testing data may be utilized to establish a relationship between a rate of change of temperature increase and a rate of change of SOC increase for various charging rates. These field testing data may then be used to determine the different coefficients for an objective function (for example, the SoC function) and constraint equations for an optimisation approach.

[0051] In an example, extensive field testing data may provide dSOCdt and dTempdt corresponding to each charging rate which may then be used to find coefficients for the SoC function and constraint equations.

[0052] In an example, the objective function may be a SoC maximization of the energy storage device 206 and a range maximization of the electric vehicle 202 within a chosen time of a hyper charging. The equations may have the constraints including a maximum allowable temperature of theenergy storage device 206 for fast charging, a maximum allowable board temperature for fast charging, a manufacturer recommended fast-charging SOC range(s), and voltage buildup limitations to provide a most optimized charging time. The fast charging with maximized SoC and user specified time herein is referred to as hypercharging.

[0053] By maximizing the charging function, the control unit 204 may also determine the charging profile. In an example, the charging profile be generated through a charging signal. Thereafter the charging profile can be transmitted to the power supply source 208 to which the energy storage device 206 is connected for charging the electric vehicle 202. In response, the control unit 204 may receive a charging current from the power supply source 208 to charge the energy storage device 206 based on the charging profile represented by the transmitted charging signal. This approach allows for a more efficient and flexible charging process that can adapt to the specific requirements and conditions of the energy storage device and the user's preferences.

[0054] In some cases, the control unit could be integrated with other systems in the electric vehicle 202, such as a vehicle's navigation system (not shown in Figure 2) or a vehicle's energy management system (not shown in Figure 2). For example, the navigation system of the electric vehicle 202 could provide information about the estimated travel time to the control unit 204, which could then adjust the charging profile to ensure that the energy storage device 204 is charged to an optimum level when the electric vehicle starts its journey.

[0055] In one example, the control unit 204 could obtain additional charging attributes of the energy storage device 206, such as a current voltage, a current capacity, or a current cycle count of the energy storage device 206. This information could be used to further optimize the charging process and to monitor the health and performance of the energy storage device 206.

[0056] The present approaches allow determining the charging profile for charging the energy storage device 206 by optimizing the SoC function with respect to the plurality of charging constraints based on charging attributes and charging characteristics of the energy storage device 206. For optimizing the SoC function and thereby provide fast-charging as compared to the electric vehicles employing constant C-rate, the electric vehicle may use any different control techniques together including rulebased, optimization based, and the data-driven approaches. In addition, the electric vehicle may utilize linear programming problem solving techniques, such as dual simplex method or graph theory method, to maximize the SoC function.

[0057] Utilizing the linear optimization techniques to optimize the increase of state of charge (SOC) based on the user defined time interval given for hypercharging in the electric vehicles, such as electric scooters provide several potential uses and applications.

[0058] By way of the disclosed technology, the users are provided with a preference to charge their electric vehicles 202 for a specified duration or a custom duration for up to a maximum time limit. The user also has the option to decide or allow the control unit 204 to determine an optimized or ideal timing while considering essential parameters that includes energy storage device dynamics (such as, the state of charge (SoC), the temperature, the charging characteristics, the charging profile, and the charging rates etc.) and other external factors. Therefore, the main objective of the present subject matter is to maximize the SoC within the time duration chosen by the user thereby providing flexibility to the user to charge the EV 202 for a preferred charging duration and keeping the temperature of the energy storage device 206 under an upper threshold.

[0059] The proposed techniques enhance the charging efficiency of the electric vehicle 202 by significantly providing an optimal SoC gain and an incremental range in the SoC which in turn does proscribe the SoC of the energy storage device 206 to hit the upper threshold of the allowabletemperature of energy storage device 206 and other threshold conditions (viz., the maximum SoC). In this manner, charging time could be significantly reduced without compromising the longevity of the energy storage device 206. Moreover, the application of such an approach, with respect to the plurality of constraints and attributes, ensure an optimized charging process that guarantees the best charging performance within the safety limits set by the energy storage device manufacturers.

[0060] Referring to FIG. 3, a flowchart outlines an exemplary method for generating a charging profile and subsequently using the charging profile for charging an energy storage device, such as the energy storage device 106 and 206, in accordance with examples of the present subject matter. The order in which the above-mentioned methods are described is not intended to be construed as a limitation, and some of the described method blocks may be combined in a different order to implement the methods, or alternative methods.

[0061] Furthermore, the above-mentioned methods may be implemented in suitable hardware, computer-readable instructions, or combination thereof. The steps of such methods may be performed by either a system under the instruction of machine executable instructions stored on a non-transitory computer readable medium or by dedicated hardware circuits, microcontrollers, or logic circuits. For example, the methods may be performed by a control unit, such as the control unit 108 or control unit 204 of the electric vehicle, such as electric vehicle 102 or electric vehicle 202, respectively. Herein, some examples are also intended to cover non-transitory computer readable medium, for example, digital data storage media, which are computer readable and encode computerexecutable instructions, where said instructions perform some or all the steps of the above-mentioned methods.

[0062] In an example, the method 300 may be implemented by the control unit to determine the charging profile 234 which is to be used for charging the energy storage device. The method begins with step 302,which involves obtaining a plurality of charging attributes of an energy storage device. In one aspect, the plurality of charging attributes may include a starting state of charge (SoC), a starting temperature of the energy storage device, and an input time provided by a user for charging the energy storage device. For example, when the energy storage device of the electric vehicle 102, 202 is discharged or expended and needs to be charged, the electric vehicle 102, 202 is connected to a power supply source, such as the power supply source 104, 208 to recharge the energy storage device. In such an instance, once the electric vehicle is plugged in for charging, the control unit 108, 204 of the electric vehicle obtains a plurality of charging attributes of the energy storage device. Examples of such plurality of charging attributes include, but are not limited to, a current SoC, a current temperature, and an input time. The current SoC and the current temperature of the energy storage device may be obtained when the energy storage device is connected to a power supply source for charging. The input time may be provided by the user via a HMI, such as the HMI 212 installed on an electric vehicle. In such a case, the user operating the electric vehicle or the person who is responsible for monitoring the charging of the electric vehicle may enter or provide a target SoC, such as the target SoC 230 on the HMI up to which the user wants to charge the energy storage device.

[0063] The method then proceeds to step 304, which involves extracting charging characteristics of the energy storage device from a data repository, such as the data repository 216. The charging characteristics may include change in SoC per minute and change in temperature per minute corresponding to a plurality of charging rates for the energy storage device. The charging characteristics are stored in the data repository based on previously conducted charging operations on the energy storage device. In some cases, the data repository may store charging characteristics of a plurality of energy storage devices segregated based on device attributessuch as charging capacity and chemical formulation of the energy storage device.

[0064] Following this, the method involves generating an SoC function indicating a linear relation between attainable SoC of the energy storage device with a SoC rise per minute corresponding to the plurality of charging rates and an individual charging time corresponding to the plurality of charging rates, as depicted in step 306. The SoC function may be defined with a specific mathematical formula and constraints. In an example, the attainable SoC function is a summation of plurality of SoC rise per minute for plurality of charging times (e.g., ti to tg) corresponding to one of the plurality of charging rates (e.g., ci to eg). For example, SoC function may written as attainable SoC = (SoC rise per min wherein ‘i’ varies from 1 to n and each ‘ti’ correspond to one of the plurality of charging rates. It may be noted that, values of ‘i’ are exemplary and it may take any of the possible values based on the possible charging rates.

[0065] The method then involves optimizing the SoC function against a plurality of charging constraints, as shown in step 308. The plurality of charging constraints incorporates the plurality of charging attributes and the charging characteristics. Post optimizing the SoC function, the method includes generating a charging profile. The charging profile may include a value of a charging parameter, such as a charging voltage, a charging temperature, a charging current, a charging time, or combination thereof.

[0066] In one aspect, the SoC function may be subjected for maximization with respect to the plurality of charging constraints using a dual simplex method to determine the maximum attainable SoC within the input time. For example, if after maximization, the control unit determines that charging of the energy storage device needs to be performed with charging-rate t1 and t5 for 5 minutes and 15 minutes, respectively. Then, the control unit may then formulate or determine the charging profile to include these details as values for the charging parameters in the charging profile.

[0067] The method then proceeds to step 310, which involves generating a charging signal representing the charging profile to be transmitted to a power supply source connected to the energy storage device for charging. The charging signal may include information about desired charging parameters, such as the charging current, the charging voltage, or the charging time.

[0068] Finally, the method involves receiving a charging current from the power supply source based on the charging profile represented in the charging signal to charge the energy storage device, as depicted in step 312. For example, the power source provides a charging current to the electric vehicle for charging the energy storage device (as depicted by arrow 240 in FIG. 2). For example, in response to transmitted charging signal, the control unit or the electric vehicle 102, 202 receives the charging current from the power source to charge the energy storage device. This approach allows for a more efficient and flexible charging process that can adapt to the specific requirements and conditions of the energy storage device and the user's preferences.

[0069] In one example, the charging constraints could include different parameters, such as a maximum allowable temperature, a maximum allowable voltage, or a maximum allowable current. The charging profile could also include different stages, such as a bulk charging stage, an absorption charging stage, and a float charging stage. The control unit could adjust the charging profile based on these constraints and stages to ensure the safety and longevity of the energy storage device.

[0070] In one example, the method for charging an energy storage device 106, 206 could include additional steps, such as calibrating the energy storage device before 106, 206 charging, performing a pre-charge check to ensure the safety of the charging process, or performing a postcharge check to verify the state of charge of the energy storage device after charging.

[0071] In one example, the charging constraints could include additional parameters, such as a maximum allowable power, a maximum allowable efficiency, or a maximum allowable cycle count of the energy storage device. The control unit 108, 204 could adjust a charging profile, such as the charging profile 230 based on these constraints to ensure the safety and efficiency of the energy storage device.

[0072] In one example, the charging profile could include different stages, such as a pre-charge stage, a main charge stage, a top-off charge stage, and a maintenance charge stage. Each of these stages could have different charging parameters and could be optimized based on the specific requirements and conditions of the energy storage and the user's preferences.

[0073] Therefore, the advantages of the present invention are that the user can select the time that they prefer for charging and the SoC will be maximized in the chosen time. Alternatively, the user can select the time that they chose for charging and the incremental range for the SoC will be maximized in the chosen time. Due to bringing a reduction in usage of charging resources, the faster charging mechanisms also holds the promise of substantial environmental benefits.

[0074] By allowing the users to choose the time along with an optimizer (such as the control unit) providing ideal charging time would precisely reduce turnaround time between charging sessions without leading to faster degradation of the health of the energy storage device.

[0075] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.

[0076] The foregoing detailed description of the illustrative embodiments thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.

Claims

I / We Claim:1 . A control unit (108, 204) to: obtain a plurality of charging attributes of an energy storage device (106, 206), wherein the plurality of charging attributes comprises a starting state of charge (SoC), a starting temperature of the energy storage device (106, 206), and an input time provided by a user for charging the energy storage device (106, 206); extract charging characteristics of the energy storage device (106, 206) from a data repository (216), wherein the charging characteristics comprises change in SoC per minute and change in temperature per minute corresponding to a plurality of charging rates for the energy storage device (106, 206); generate an SoC function indicating linear relation between attainable SoC of the energy storage device (106, 206) with a SoC rise per minute corresponding to the plurality of charging rates and an individual charging time corresponding to the plurality of charging rates; and optimize the SoC function against a plurality of charging constraints, with the plurality of charging attributes and charging characteristics incorporated within the plurality of charging constraints; and generate a charging profile based on the optimized SoC function, wherein the charging profile comprises a value of a charging parameter.

2. The control unit (108, 204) as claimed in claim 1 , wherein the charging parameter is one of a charging voltage, a charging temperature, a charging current, a charging time, or combination thereof.

3. The control unit (108, 204) as claimed in claim 1 , wherein the current SoC and current temperature of the energy storage device (106, 206) are obtained when the energy storage device (106, 206) is connected to a power supply source (104, 208) for charging.

4. The control unit (108, 204) as claimed in claim 1 , wherein the input time is provided by the user via a Human Machine interface (HMI) (212) installed on an electric vehicle (102, 202).

5. The control unit (108, 204) as claimed in claim 1 , wherein to subject the SoC function to be optimized, the control unit (108, 204) is to: subject the SoC function for maximization with respect to the plurality of charging constraints using a dual simplex method to determine the maximum attainable SoC within the input time.

6. The control unit (108, 204) as claimed in claim 5, wherein the SoC function is: attainable SoC = (SoC rise per m in)i * ts, wherein ‘i’ varies from 1 to 9 and each£ts’ correspond to one of the plurality of charging rates; wherein the plurality of charging constraints comprises:AJemp <= tempjimit - start temperature;Total charging time <= input time;A_SoC >= min((temp_limit - start temperature)*f, X3 - Start SoC);A_SoC X1 >= max(min(X1 , X3) - max(start SoC, X2), 0);A_SoC X2 <= max(min(X2, X3) - start SoC, 0); and tempjimit - start temperature; wherein temp imit is the maximum allowable temperature of the energy storage device (106) for charging, start temperature is the temperature of energy storage device (106, 206) at the start of the charging session, input time is the time selected by the user for performing charging, start SoC is the SoC at the start of the charging session, ‘f is the factor based on the ratio of temperature change per minute to the SoC change per minute of the lowest charging rate, ‘XT is the SoC above which certain charging rates are not allowed due to voltage buildup constraints, X2’ is the SoC below which only certain C rates are allowed, ‘X3’ is the maximum allowable SoC limit for charging, total charging time is sum of charging times for each of thec-rates possible, A_temp is the increase in temperature of the battery pack during the proposed charging cycle.

7. The control unit (108, 204) as claimed in claim 1 , wherein the control unit (108, 204) is to: generate a charging signal, representing the charging profile, to be transmitted to a power supply source (104, 208) to which the energy storage device (106, 206) is connected for charging; and receive a charging current from the power supply source (104, 208) to charge the energy storage device (106, 206) based on the transmitted charging signal.

8. The control unit (108, 204) as claimed in claim 1 , wherein to extract the charging characteristics of the energy storage device (106, 206), the control unit (108, 204) is to: determine a plurality of device attributes of the energy storage device (106, 206), wherein the plurality of device attributes comprise charging capacity and chemical formulation of the energy storage device (106, 206); and select the charging characteristics of the energy storage device (106, 206) from the data repository (216) based on the plurality of device attributes, wherein the data repository (216) stores the charging characteristics of a plurality of energy storage devices segregated based on device attributes.

9. A method comprising: obtaining a plurality of charging attributes of an energy storage device (106, 206), wherein the plurality of charging attributes comprises a starting state of charge (SoC), a starting temperature of the energy storage device (106, 206), and an input time provided by a user for charging the energy storage device (106, 206); extracting charging characteristics of the energy storage device (106, 206) from a data repository (216), wherein the charging characteristics comprises change in SoC per minute and change in temperature per minutecorresponding to a plurality of charging rates for the energy storage device (106, 206); generating an SoC function indicating linear relation between attainable SoC of the energy storage device (106, 206) with a SoC rise per minute corresponding to the plurality of charging rates and an individual charging time corresponding to the plurality of charging rates; and optimizing the SoC function against a plurality of charging constraints, with the plurality of charging attributes and charging characteristics incorporated within the plurality of charging constraints; and generating a charging profile based on the optimized SoC function, wherein the charging profile comprises a value of a charging parameter.

10. The method as claimed in claim 9, wherein the charging parameter is one of a charging voltage, a charging temperature, a charging current, a charging time or combination thereof.

11. The method as claimed in claim 9, wherein the current SoC and current temperature of the energy storage device (106, 206) are obtained when the energy storage device (106, 206) is connected to a power supply source (104, 208) for charging.

12. The method as claimed in claim 9, wherein the input time is provided by the user via a Human Machine interface (HMI) (212) installed on an electric vehicle (102, 202).

13. The method as claimed in claim 9, wherein while subjecting the SoC function to be optimized, the method comprises: subjecting the SoC function for maximization with respect to the plurality of charging constraints using a dual simplex method to determine the maximum attainable SoC within the time period provided by the user; wherein the SoC function is : attainable SoC = (SoC rise per m in)i * ts, wherein ‘i’ varies from 1 to 9 and each£ts’ correspond to one of the plurality of charging rates; wherein the plurality of charging constraints comprises:A_temp <= temp imit - start temperature;Total charging time <= input time;A_SoC >= min((temp_limit - start temperature)*f, X3 - Start SoC);A_SoC X1 >= max(min(X1 , X3) - max(start SoC, X2), 0); A_SoC X2 <= max(min(X2, X3) - start SoC, 0); and temp imit - start temperature; wherein tempjimit is the maximum allowable temperature of the energy storage device (106, 206) for charging, start temperature is the temperature of energy storage device (106, 206) at the start of the charging session, input time is the time selected by the user for performing charging, start SoC is the SoC at the start of the charging session, ‘f is the factor based on the ratio of temperature change per minute to the SoC change per minute of the lowest charging rate, ‘XT is the SoC above which certain charging rates are not allowed due to voltage buildup constraints, X2’ is the SoC below which only certain C rates are allowed, ‘X3’ is the maximum allowable SoC limit for charging, total charging time is sum of charging times for each of the c-rates possible, A emp is the increase in temperature of the battery pack during the proposed charging cycle.

14. The method as claimed in claim 9, wherein the method comprises: generating a charging signal representing the charging profile to be transmitted to a power supply source (104, 208) connected to which the energy storage device (106, 206) is connected for charging; and receiving a charging current from the power supply source (104, 208) to charge the energy storage device (106, 206) based on the charging signal.

15. The method as claimed in claim 9, wherein for extracting the charging characteristics of the energy storage device (106, 206), the method comprises: determining a plurality of device attributes of the energy storage device (106, 206), wherein the plurality of device attributes comprisecharging capacity and chemical formulation of the energy storage device (106, 206); and selecting charging characteristics of the energy storage device (106, 206) from the data repository (216) based on the plurality of device attributes, wherein the data repository (216) stores charging characteristics of a plurality of energy storage device (106, 206) segregated based on device attributes.

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