EV charging optimization by charging perturbation across fleet of electric vehicles on road

Abstract

Systems and methods for optimizing a charging protocol across a team of electric vehicles over time are disclosed. In particular, the cloud backend generates one or more replaceable or experimental charging protocols by perturbing a baseline charging profile of a baseline charging protocol. A "perturbation" charging protocol is deployed to a subset of the fleet of electric vehicles. As a subset of the fleet of electric vehicles uses a perturbation charging protocol to charge their batteries, the cloud backend observes the effects of the perturbation charging protocol on battery aging and charging time based on battery data received from the subset of the fleet of electric vehicles. Based on these battery data, the cloud backend revises and improves a baseline charging protocol deployed to the entire team of the electric vehicle.

Description

Technical Field

[0001] The apparatus and methods disclosed in this document relate to battery charging, and more particularly to optimizing electric vehicle charging across a fleet of electric vehicles. Background Art

[0002] Unless otherwise indicated herein, the materials described in this section are not admitted to be prior art by inclusion in this section.

[0003] The specific charging protocol(s) used to charge the batteries of an electric vehicle may have a significant impact on the long-term degradation of the batteries. In particular, this is the case when the electric vehicle is charged at high power using a DC fast charger. The charging current used to charge the batteries in an electric vehicle is typically regulated by a battery management system (BMS) on the electric vehicle, which implements the charging protocol(s). Typically, the charging protocol(s) deployed on the BMS are designed by the battery manufacturer before the vehicle is released. The charging protocol typically takes the form of a static graph of the charging current as a function of the battery temperature and the battery voltage. The charging protocol(s) are generally designed to maximize the charging speed without a significant impact on battery degradation.

[0004] However, because these charging protocol(s) are experimentally derived under laboratory conditions, they are not necessarily optimized for real-world operation across a wide variety of operating conditions. Thus, these charging protocol(s) may be too conservative under certain conditions (providing a slower charge than necessary) and may be too aggressive under certain conditions (causing faster than desired battery aging). Further, batteries degrade during use, and a static BMS charging map, even if optimal at the beginning of life, may no longer be optimal in terms of charging time and / or aging. Therefore, it would be advantageous to have a method for adapting a baseline charging profile derived under a laboratory setting based on real-world battery performance and aging observed on the road. Summary of the invention

[0005] A method for adapting a charging protocol for charging batteries of a plurality of electric vehicles. The method comprises storing a baseline charging protocol in a memory of a server. The method further comprises determining, with a processor of the server, a plurality of alternative charging protocols by modifying the baseline charging protocol. The method further comprises transmitting, with a transceiver of the server, a respective alternative charging protocol from the plurality of alternative charging protocols to each respective electric vehicle from a subset of the plurality of electric vehicles, the subset of the plurality of electric vehicles being configured to charge their batteries according to the plurality of alternative charging protocols. The method further comprises receiving, with the transceiver, battery data from the subset of the plurality of electric vehicles, the battery data having been measured during or after charging the batteries of the subset of the plurality of electric vehicles according to the plurality of alternative charging protocols. The method further comprises updating, with the processor, the baseline charging protocol based on the battery data.

[0006] A method for adapting a charging protocol for charging a battery of an electric vehicle is disclosed. The method comprises: receiving, using a transceiver of a battery management system, an alternative charging protocol from a server. The method further comprises: controlling, using a processor of the battery management system, the charging of the battery according to the alternative charging protocol. The method further comprises: measuring, using at least one sensor of the battery management system, battery data during or after charging the battery according to the alternative charging protocol. The method further comprises: transmitting, using the transceiver, the battery data to the server. The method further comprises: receiving, using the transceiver, an updated baseline charging protocol, the updated baseline charging protocol having been determined based on the battery data and further battery data from a further electric vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The above aspects and other features of the method are explained in the following description taken in conjunction with the accompanying drawings.

[0008] Figure 1 An exemplary embodiment of a system for optimizing battery charging protocols across a fleet of electric vehicles is shown.

[0009] Figure 2 An exemplary battery charging system for an electric vehicle is shown.

[0010] Figure 3 Exemplary components of a cloud backend are shown.

[0011] Figure 4A method for optimizing battery charging protocols across a fleet of electric vehicles is shown.

[0012] Figure 5 Exemplary baseline and perturbation current-voltage profiles for specific battery temperatures are shown. DETAILED DESCRIPTION

[0013] For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the embodiments illustrated in the accompanying drawings and described in the following written description. It should be understood that, thereby, no limitation to the scope of the present disclosure is intended. It should be further understood that the present disclosure includes any changes and modifications to the illustrated embodiments, and includes further applications of the principles of the present disclosure as would normally occur to a person skilled in the art to which the present disclosure belongs.

[0014] System Overview Figure 1 An exemplary embodiment of a system 100 for optimizing battery charging protocols across a fleet of electric vehicles is shown. The system 100 includes a plurality of electric vehicles 102 (only one is illustrated for simplicity) and a cloud backend 120. As will be discussed in more detail below, the cloud backend 120 advantageously operates to continuously adapt and improve the charging protocol(s) utilized by the electric vehicles 102 in the fleet.

[0015] Each electric vehicle 102 in the fleet includes at least one battery 104 that is rechargeable and configured to provide power to a drive system (not shown) of the electric vehicle 102. In at least some embodiments, the battery 102 is a lithium-ion battery pack composed of multiple individual cells connected in series and parallel to achieve a desired voltage and capacity. The battery 102 can be located, for example, under the floor or seat of the electric vehicle.

[0016] In addition, each electric vehicle 102 further includes a battery management system (BMS) 110 configured to monitor the individual cell performance, temperature, and overall health of the battery 104. In addition, the BMS 110 is configured to implement the following charging protocol: The charging protocol is used to optimize the charging (and discharging) process of the battery 102 to minimize the charging time of the battery 102, maximize the life of the battery 102, and ensure that the battery 102 operates within safe limits. To this end, the BMS 110 is configured to: Figure 2 ) receives sensor data; and operates the charging circuit 112 to charge the battery 102 according to a given charging protocol.

[0017] The cloud backend 120 is configured to optimize the charging protocol across the fleet of electric vehicles 102 over time. In particular, the cloud backend 120 is configured to generate one or more alternative or experimental charging protocols by perturbing the baseline charging profile of the baseline charging protocol and deploying the "perturbed" charging protocol to a subset of the fleet of electric vehicles 102. As the subset of the fleet of electric vehicles 102 uses the perturbed charging protocol to charge its batteries 104, the cloud backend 120 observes the impact of the (one or more) perturbed charging protocols on battery aging and charging time by means of battery data received from the subset of the fleet of electric vehicles 102. Based on these battery data, the cloud backend 120 revises and improves the baseline charging protocol deployed to the entire fleet of electric vehicles 102.

[0018] Exemplary Hardware Embodiment Figure 2 An exemplary battery charging system 200 for an electric vehicle 102 is shown. The system 200 includes the battery charging system 200 described above. Figure 1 Reference is made to battery 104, BMS 110, and charging circuit 112. It should be appreciated that the components of battery charging system 200 described herein are merely exemplary, and battery charging system 200 may include any alternative configurations.

[0019] The battery 104 is configured to store electrochemical energy. The battery 104 includes one or more electrochemical cells 204 arranged in parallel and / or in series to form the battery 104. In one embodiment, the battery 104 is a lithium-ion battery pack, and the electrochemical cell 204 is a lithium-ion cell. The battery 104 includes a positive battery terminal 206 and a negative battery terminal 208, via which the battery 104 provides an output voltage and an output current. In addition, the battery 104 is configured to be charged via the positive and negative battery terminals 206, 208.

[0020] The system 200 further includes a power source 210 and a charging circuit 112. The power source 210 is configured to apply a charging current and / or a charging voltage to the battery 104 via the positive and negative battery terminals 206, 208 during the charging process. In some embodiments, the power source 210 is configured to provide a predetermined constant direct current (DC) voltage or current. In some embodiments, the power source 210 is an alternating current (AC) voltage or current source. In one embodiment, the power source 210 is a local power grid (mains) configured to provide a single-phase or three-phase AC voltage with a predetermined frequency (such as 50 Hz or 60 Hz) and a predetermined nominal voltage (such as a nominal voltage between 110-127 volts or 220-240 volts).

[0021] The charging circuit 112 is connected between the power source 210 and the battery 104 and is configured to convert, regulate and / or control the charging current and / or charging voltage applied to the battery 104 by the power source 210. In some embodiments, the charging circuit 112 includes: a charging controller 214, which operates various power electronic devices 216 to convert, regulate and / or control the charging current and / or charging voltage applied to the battery 104. The power electronic devices 216 include: various circuits and hardware, which may include, for example, contactors, relays, transistors, transformers, diodes, capacitors, inductors, and resistors arranged in a conventional manner. In some embodiments, additional power conversion circuits, such as separate AC / DC converters, may be arranged between the power source 210 and the charging circuit 112.

[0022] The charging controller 214 may be a component of the BMS 110 or a separate component that receives commands from the BMS 110 for the purpose of controlling the charging process of the battery 104 according to a specific charging protocol. It should be recognized by those skilled in the art that a "controller" includes any hardware system, hardware mechanism, or hardware component that processes data, signals, or other information. Thus, the charging controller 214 may include a system having a central processing unit, multiple processing units, dedicated circuits for implementing specific functions, or other systems.

[0023] The BMS 110 includes a processor 230 configured to execute program instructions stored on a memory 236. The memory 236 stores at least program instructions configured to implement the charging protocol 236 and any data required therefor, such as a current-voltage profile, a current-temperature profile, and / or an equivalent lookup table. The memory 236 may belong to any type of device capable of storing information accessible to the BMS 110, such as a memory card, ROM, RAM, a writable memory, a read-only memory, a hard drive, a disk, a flash memory, or any of a variety of other computer-readable media that act as a data storage device as those skilled in the art should recognize. In addition, those skilled in the art should recognize that a "processor" includes any hardware system, hardware mechanism, or hardware component that processes data, signals, or other information. Therefore, the BMS 110 may include a system having a central processing unit, a multi-processing unit, a dedicated circuit or other system for implementing a specific function.

[0024] The BMS 110 further includes: at least one network communication module 234, which provides an interface for communicating with any of various other devices including at least the cloud backend 120. The network communication module 234 may include one or more transceivers, modems, processors, memories, oscillators, antennas, or other hardware that is traditionally included in a communication module to enable communication with various other devices. In particular, the network communication module 336 generally includes one or more cellular modems configured to communicate with a wireless telephone network, but may further include a Bluetooth A module (not shown) and / or a Wi-Fi module configured to enable communication with a Wi-Fi network and / or a Wi-Fi router (not shown). Communication may be accomplished using any of a variety of known communication protocols.

[0025] The system 200 further includes a current sensor 218, a voltage sensor 220, and a temperature sensor 222, respectively, configured to monitor the battery current, battery voltage, and battery temperature at least during the charging / discharging process. The BMS 110 is operably connected to the current sensor 218, the voltage sensor 220, and the temperature sensor 222, and is configured to receive measurement signals corresponding to the battery current, the battery voltage, and the battery temperature. In one embodiment, the current sensor 218 includes: a shunt resistor arranged in series with the battery 104, which provides a voltage proportional to the battery current. In one embodiment, the current sensor 218 includes: a Hall effect sensor, arranged in series with the battery 104 and configured to measure the battery current. The voltage sensor 220 is connected in parallel with the battery 104 and is configured to measure the battery voltage across the positive and negative battery terminals 206, 208 of the battery 104. In some embodiments, the voltage sensor is further configured to measure the voltage of the individual cells 204 of the battery 104. In some embodiments, processor 230 is configured to determine, calculate and / or estimate further battery parameters, such as state of charge, state of health, impedance, capacity, open circuit voltage and / or resting voltage.

[0026] Figure 3Exemplary components of the cloud backend 120 are shown. The cloud backend 120 includes one or more cloud servers 300 and one or more databases 320. The cloud servers 300 may include servers configured to serve a variety of functions for the cloud backend 120, but at least include one or more servers configured to perform the following operations: managing battery data received from the BMS 110 of the fleet of electric vehicles; and optimizing the (one or more) charging protocols used by the fleet of electric vehicles 102 to charge their batteries 104. Each of the cloud servers 300 includes, for example, a processor 302, a memory 304, a user interface 306, and a network communication module 308. It should be appreciated that the illustrated embodiment of the cloud server 300 is only one exemplary embodiment of the cloud server 300 and represents only any of the various modes or configurations of a personal computer, a server, or any other data processing system operating in the manner set forth herein.

[0027] The processor 302 is configured to execute instructions for operating the cloud server 300 to implement features, functions, characteristics, etc. as described herein. To this end, the processor 302 is operably connected to the memory 304, the user interface 306, and the network communication module 308. The processor 302 generally includes one or more processors that can operate in parallel or otherwise in unison with each other. It should be appreciated by those skilled in the art that a "processor" includes any hardware system, hardware mechanism, or hardware component that processes data, signals, or other information. Therefore, the processor 302 may include a system with a central processing unit, a graphics processing unit, a multi-processing unit, a dedicated circuit for implementing a function, a programmable logic, or other processing system.

[0028] The database 320 is configured to store battery data received from the BMS 110. The database 320 may belong to any type of long-term non-volatile storage device capable of storing information accessible to the processor 302, such as a hard drive or any of a variety of other computer-readable storage media recognized by those skilled in the art. Similarly, the memory 304 is configured to store program instructions that, when executed by the processor 302, enable the cloud server 300 to perform various operations described herein, including optimizing the charging protocol (s) used by the fleet of electric vehicles 102 to charge their batteries. In addition, as will be discussed in more detail below, the memory 304 stores a baseline charging protocol 310 and one or more perturbation charging protocols 312. The memory 304 may belong to any type of device or combination of devices capable of storing information accessible to the processor 302, such as a memory card, ROM, RAM, hard drive, disk, flash memory, or any of a variety of other computer-readable media recognized by those skilled in the art.

[0029] The network communication module 308 of the cloud server 300 provides an interface that allows communication with any of the various devices including at least the BMS 110. In particular, the network communication module 308 may include: a local area network port that allows communication with any of the various local computers housed in the same or nearby facilities. Generally, the cloud server 300 communicates with the remote computer on the Internet via a separate modem and / or router of the local area network. Alternatively, the network communication module 308 may further include: a wide area network port that allows communication on the Internet. In one embodiment, the network communication module 308 is equipped with a Wi-Fi transceiver or other wireless communication device. Accordingly, it should be appreciated that communication with the cloud server 300 can occur via wired communication or via wireless communication. Any of a variety of known communication protocols can be used to complete the communication.

[0030] The cloud server 300 can be operated locally or remotely by an administrator. To facilitate local operation, the cloud server 300 can include a user interface 306. In at least one embodiment, the user interface 306 can suitably include an LCD display screen, etc., a mouse or other pointing device, a keyboard or other keypad, a speaker, and a microphone, as will be appreciated by those skilled in the art. Alternatively, in some embodiments, an administrator can operate the cloud server 300 away from another computing device that communicates with it via a network communication module 308 and has a similar user interface.

[0031] The cloud backend 120 is configured to store and manage battery data on the database 320 in a secure manner and to provide access to the battery data for the purpose of optimizing the charging protocol(s) used by a fleet of electric vehicles 102 to charge their batteries. The memory 304 stores program instructions for optimizing battery charging protocols across a fleet of electric vehicles.

[0032] Method for optimizing battery charging protocols across a fleet of electric vehicles Various methods and processes for operating the BMS 110 and the cloud backend 120 are described below. In these descriptions, statements that a method, processor, and / or system performs a task or function refer to a controller or processor (e.g., the processor 230 of the BMS 110 or the processor 302 of the cloud backend 120) executing programming instructions stored in a non-transitory computer-readable storage medium (e.g., the memory 232 of the BMS 110 or the memory 304 of the cloud storage backend 120) operatively connected to the controller or processor to manipulate data or operate one or more components in the system 100 to perform a task or function. In addition, the steps of the method may be performed in any feasible time order, regardless of the order shown in the various figures or the order in which the steps are described.

[0033] Figure 4 A method 400 for optimizing battery charging protocols across a fleet of electric vehicles is shown. Advantageously, the method adapts and improves the charging protocol(s) deployed on a fleet of electric vehicles 102 over time based on real-world data from the fleet.

[0034] The method 400 begins by storing a baseline charging protocol for charging the batteries of a fleet of electric vehicles at a server (box 410). In particular, the cloud backend 120 stores the baseline charging protocol 310 in the memory 304. The baseline charging protocol 310 is also deployed to the BMS 110 of each electric vehicle 102 in the fleet. As discussed above, the baseline charging protocol 310 may be, for example, initially designed by a battery manufacturer before the electric vehicle 102 is released and initially deployed on the BMS 110 at the time of manufacturing. Alternatively, the baseline charging protocol 310 may be designed based on laboratory testing or a battery model, and the baseline charging protocol 310 may be subsequently deployed in the BMS 110 of each electric vehicle 102 by transmitting the baseline charging protocol 310 to the BMS 110 of each electric vehicle 102 using the network communication module 308.

[0035] In at least some embodiments, the baseline charging protocol 310 includes controlling the charging current as a function of the battery voltage and the battery temperature or as a function of the battery state of charge and the battery temperature, as expressed by one or more charging profiles. In particular, the baseline charging protocol 310 may include charging the battery 102 according to a baseline current-voltage profile. In addition, the baseline charging protocol 310 may further include charging the battery 102 according to a baseline current-temperature profile. Finally, the baseline charging protocol 310 may further include charging the battery 102 according to a baseline current-SOC profile. In at least one embodiment, the baseline charging protocol 310 is characterized by a plurality of baseline current-voltage profiles corresponding to a plurality of different battery temperatures. In another embodiment, the baseline charging protocol 310 is characterized by a plurality of baseline current-SOC profiles corresponding to a plurality of different battery temperatures. For a given battery temperature, the baseline charging protocol 310 charges the battery 102 according to a baseline current-temperature profile associated with the given battery temperature. In some embodiments, each charging profile is embodied by a lookup table that provides a charging current in consideration of a particular battery voltage and / or battery temperature. Alternatively, in other embodiments, each charging profile is embodied as a mathematical function and / or equation.

[0036] Figure 5An exemplary baseline current-voltage profile 500 for a particular battery temperature is shown. As can be seen, the baseline current-voltage profile 500 has a stair-step-like shape including segments in which different ranges of battery voltage correspond to different constant charging currents. As can be seen, a relatively high charging current is applied in response to a relatively low battery voltage, and a relatively low charging current is applied relative to a relatively high battery voltage, resulting in an overall negative slope for the baseline current-voltage profile 500. However, it should be appreciated that the charging current profile may be non-monotonic (e.g., starting at a lower current and then increasing before decreasing again). In addition, it should be appreciated that although the exemplary baseline current-voltage profile 500 has a stair-step-like shape (which will generally facilitate easier implementation by the BMS 110 and / or the charging controller 214), the baseline current-voltage profile may have a variety of shapes and patterns. As noted above, multiple such baseline current-voltage profiles may be provided for multiple different battery temperatures.

[0037] Return to Figure 4 , the method 400 continues to determine a plurality of perturbed charging protocols by perturbing the baseline charging protocol at the server (block 420). In particular, the processor 302 of the cloud backend 120 determines a plurality of perturbed charging protocols 312 by modifying the baseline charging protocol 310. The perturbed charging protocol 312 may also be referred to herein as an alternative charging protocol, a modified charging protocol, or an experimental charging protocol. The processor 302 determines a plurality of perturbed charging protocols 312 by modifying at least one baseline current-voltage profile (and / or at least one baseline current-temperature profile) of the baseline charging protocol 310.

[0038] Each perturbation charging protocol 312 includes one or both of a perturbation current-voltage profile and a perturbation current-temperature profile, both of which incorporate small deviations from the profile of the baseline charging protocol while maintaining substantially similar charging times so that there is no discernible impact on the driver experience. In particular, in at least some embodiments, each perturbation charging protocol 312 is characterized by a plurality of perturbation current-voltage profiles corresponding to a plurality of different battery temperatures. These perturbation charging protocols 312, in particular, perturbation current-voltage profiles and / or current-temperature profiles, can be derived in a variety of ways.

[0039] In at least one embodiment, the processor 302 of the cloud backend 120 determines a plurality of perturbation charging protocols 312 by applying a battery model to find an alternative current-voltage profile and / or current-temperature profile that is expected to result in a charging time within a predetermined threshold difference from the charging time generated by the baseline current-voltage profile. The predetermined threshold difference in the resulting charging time may be defined as within + / -15% of the baseline charging time of the baseline charging protocol 310, more particularly within + / -10% of the baseline charging time of the baseline charging protocol 310, or even more particularly within + / -5% of the baseline charging time of the baseline charging protocol 310. In some embodiments, the processor 302 modifies parameters of the battery model (such as for internal state limits of the battery) to derive the plurality of perturbation charging protocols 312.

[0040] In another embodiment, the processor 302 of the cloud backend 120 determines multiple perturbation charging protocols 312 by the following operations: discretizing the baseline current-voltage distribution diagram and / or the current-temperature distribution diagram, and randomly or programmatically modifying the values ​​of the baseline current-voltage distribution diagram and / or the current-temperature distribution diagram according to a certain set of rules, which ensures that the modified current-voltage distribution diagram and / or the current-temperature distribution diagram are expected to obtain similar charging times when used to charge the battery 104.

[0041] Reference again Figure 5 , exemplary perturbed current-voltage profiles 502, 504, and 506 of an exemplary perturbed charging protocol for a particular battery temperature are shown. Much like the baseline current-voltage profile 500, the exemplary current-voltage profiles 502, 504, and 506 are stair-step-like shapes that include segments in which the range of battery voltages corresponds to a constant current, but with small changes to both the voltage threshold and the charging current to be applied during a particular step. However, it should be appreciated that the perturbed current-voltage profiles 502, 504, and 506 can have a wide variety of other shapes and patterns. Furthermore, as noted above, a plurality of such perturbed current-voltage profiles can be provided for a plurality of different battery temperatures.

[0042] Return to Figure 4, the method 400 continues by providing the perturbation charging protocol to a subset of the fleet of electric vehicles (block 430). In particular, the processor 302 of the cloud backend 120 selects a subset of electric vehicles 102 from the fleet of electric vehicles 102. Next, the processor 302 operates the network communication module 308 to transmit a corresponding one of the perturbation charging protocols 312 to each electric vehicle 102 in the subset of electric vehicles 102. At each corresponding electric vehicle 102 in the subset of electric vehicles 102, its BMS 110 receives the corresponding one of the perturbation charging protocols 312 from the cloud backend 120 via its network communication module 234 and stores it in the memory 232 (i.e., as the charging protocol 236).

[0043] In some embodiments, the processor 302 selects the subset of electric vehicles 102 as a random subset of the fleet of electric vehicles 102. Alternatively, in some further embodiments, the processor 302 selects the subset of electric vehicles 102 according to one or more of the observed environmental conditions of the electric vehicles 102, the observed driving style of the electric vehicles 102, and / or the observed charging behavior of the electric vehicles 102. To this end, in some embodiments, the processor 230 of the BMS 110 of each electric vehicle 102 is configured to: continuously monitor and record data related to environmental conditions, driving style, and / or charging behavior. The processor 230 operates its network communication module 234 to transmit the data to the cloud backend 120, which receives it via the network communication module 308. The processor 302 of the cloud backend 120 can select a subset of electric vehicles 102 according to the data related to environmental conditions, driving style, and / or charging behavior.

[0044] Typically, a subset of the fleet of electric vehicles 102 is a small portion of the entire fleet of electric vehicles 102, for example, 5-10% of the overall size of the fleet. The subset of electric vehicles 102 should be large enough to provide a representative sample of the environmental conditions, driving style, and / or charging behavior of the fleet as a whole.

[0045] The method 400 continues with charging the batteries of a subset of the fleet of electric vehicles using the perturbation charging protocol (block 440). In particular, after the perturbation charging protocol 312 is provided to the subset of the fleet of electric vehicles 102, the BMS 10 of each vehicle 102 in the subset is configured to charge the battery 104 using a corresponding received one of the perturbation charging protocols 312. The BMS 10 commands the charge controller 214 to operate the power electronics 216 in such a manner as to control the charging current according to the corresponding received one of the perturbation charging protocols 312.

[0046] During the charging process, the BMS 10 and / or the charging controller 214 sets the charging current according to the current battery temperature and the current battery voltage according to the (one or more) perturbation current-voltage profiles and / or (one or more) perturbation current-temperature profiles of the corresponding received one in the perturbation charging protocol 312. In at least one embodiment, the perturbation charging protocol 312 defines a plurality of current-voltage profiles, each associated with a different corresponding battery temperature. The BMS 10 and / or the charging controller 214 selects a corresponding one of the current-voltage profiles according to the current battery temperature, and then sets the charging current according to the current battery voltage based on the selected current-voltage profile.

[0047] The batteries 104 of a subset of the fleet of electric vehicles 102 are charged for a predetermined period of time, such as a predetermined number of weeks or months, using the perturbation charging protocol 312. During the predetermined period of time, there is no adverse impact on the driver experience for the subset of the fleet of electric vehicles 102 because the perturbation to the baseline charging protocol 310 is small and results in similar charging times.

[0048] The method 400 continues to measure battery data during or after charging the battery using the perturbation charging protocol (block 450). During a predetermined time period, in addition to charging the battery 104 using a corresponding received one of the perturbation charging protocols 312, the BMS 10 also operates the sensors 218, 220, 222 to collect a plurality of battery data for the purpose of observing the effect of the perturbation charging protocol 312 on battery aging. As used herein, "battery data" refers to any sensor data related to the performance, health, and / or aging of a battery. These battery data may include, for example, battery current, battery voltage, and battery temperature measured over time during or after charging the battery 104 using one of the perturbation charging protocols 312. These battery data may be collected for the battery 104 as a whole or for individual cells of the battery 104. In some embodiments, the BMS 10 will derive further battery data, such as a state of charge or other metrics of the battery 104, based on the directly measured sensor data from the sensors 218, 220, 222. This data can then be used to estimate the battery state of health during operation and track how that state of health changes over a monitoring period of weeks or months.

[0049] Based on tracking the health state for this subset of the fleet over a certain period of time, the local gradient with respect to the objective / cost function of the charging protocol (battery aging rate) can be calculated, and potential directions can be derived in which their current-voltage and / or current-temperature distribution maps should be updated to improve the optimality of the objective function.

[0050] The method 400 continues by providing the battery data to the server (block 460). At each respective electric vehicle 102 in the subset of electric vehicles 102, the processor 230 of the respective BMS 110 operates its network communication module 234 to transmit the battery data collected during the predetermined time period to the cloud backend 120. The cloud backend 120 receives the respective battery data from each vehicle in the subset of electric vehicles 102 and stores the battery data in the database 320.

[0051] The method 400 continues by updating the baseline charging protocol based on the battery data (block 470). In particular, the processor 302 of the cloud backend 120 updates the baseline charging protocol 310 based on the battery data received from the subset of electric vehicles 102 and based on the associated perturbation charging protocol 312. In some embodiments, the processor 203 determines a modification to the baseline charging protocol 310 that will result in at least one of: (i) slower battery aging and (ii) faster charging time compared to the baseline charging protocol 310. In at least one embodiment, the processor 302 updates the baseline charging protocol 310 using a predetermined objective / cost function that optimizes charging time and battery aging.

[0052] In at least one embodiment, processor 302 identifies a perturbed charging protocol from the plurality of perturbed charging protocols 312 that results in at least one of: (i) slower battery aging and (ii) faster charging time compared to the baseline charging protocol. Processor 302 then determines a modification to baseline charging protocol 310 based on the identified one of perturbed charging protocols 312.

[0053] In at least one embodiment, the processor 302 of the cloud backend 120 determines updated internal state limits for the battery 104 based on the received battery data and / or based on the identified one of the perturbation charging protocols 312. The processor 302 then updates the baseline charging protocol 310 using the updated internal state limits by applying the battery model.

[0054] In another embodiment, the processor 302 of the cloud backend 120 determines one or more gradients based on the battery data received in association with each perturbation charging protocol 312. The processor 302 then updates the baseline charging protocol 310 based on the gradient(s) using a gradient-based update method.

[0055] The method 400 continues by providing the updated baseline charging protocol to the fleet of electric vehicles (block 480). In particular, the processor 302 of the cloud backend 120 operates its network communication module 308 to transmit the updated baseline charging protocol to all or at least some of the electric vehicles 102 in the fleet of electric vehicles 10. At each electric vehicle 102, the BMS 110 receives the updated baseline charging protocol from the cloud backend 120 via its network communication module 234 and stores it in the memory 232 (i.e., as the charging protocol 236).

[0056] Once provided with the updated baseline charging protocol, the BMS 10 charges the battery 104 using the updated baseline charging protocol, thereby advantageously providing improved performance and / or reduced aging of the battery 104 .

[0057] The above process may be iterated periodically to further update the baseline charging protocol. In particular, in each iteration of the method, a new subset of electric vehicles 102 is selected from the fleet of electric vehicles 102, and a new plurality of perturbation charging protocols are generated. In this way, the charging protocol may be continuously adapted and improved throughout the life of the vehicles 102 in the fleet. Further, new vehicles deployed on the road may be provided directly with an updated baseline charging protocol, rather than the original baseline protocol, thereby providing direct benefits to those drivers.

[0058] Embodiments within the scope of the present disclosure may also include non-transient computer-readable storage media or machine-readable media for carrying or storing thereon computer-executable instructions (also referred to as program instructions) or data structures. This non-transient computer-readable storage media or machine-readable media may be any available medium that can be accessed by a general or special-purpose computer. As an example and not limitation, this non-transient computer-readable storage media or machine-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or may be used for carrying or storing any other medium of desired program code device in the form of computer-executable instructions or data structures. The combination of the above items also should be included in the scope of non-transient computer-readable storage media or machine-readable media.

[0059] Computer executable instructions include, for example, instructions and data that cause a general purpose computer, a special purpose computer, or a special purpose processing device to perform a certain function or group of functions. Computer executable instructions also include program modules that are executed by computers in a stand-alone or network environment. In general, program modules include routines, programs, objects, components, and data structures that perform specific tasks or implement specific abstract data types. Computer executable instructions, associated data structures, and program modules represent examples of program code means for performing the steps of the methods disclosed herein. A specific sequence of such executable instructions or associated data structures represents an example of corresponding actions for implementing the functions described in such steps.

[0060] Although the present disclosure has been illustrated and described in detail in the drawings and the above description, the present disclosure should be considered as appropriately illustrative rather than restrictive. It should be understood that only preferred embodiments have been presented, and all changes, modifications and further applications falling within the spirit of the present disclosure are desired to be protected.

Claims

1. A method for adapting a charging protocol for charging batteries of a plurality of electric vehicles, the method comprising: storing a baseline charging protocol in a memory of the server; determining, with a processor of the server, a plurality of alternative charging protocols by modifying the baseline charging protocol; transmitting, with a transceiver of the server, a respective alternative charging protocol from the plurality of alternative charging protocols to each respective electric vehicle from a subset of the plurality of electric vehicles, the subset of the plurality of electric vehicles being configured to charge their batteries according to the plurality of alternative charging protocols; receiving, with the transceiver, battery data from a subset of the plurality of electric vehicles, the battery data having been measured during or after charging batteries of the subset of the plurality of electric vehicles according to the plurality of alternative charging protocols; as well as The baseline charging protocol is updated, with the processor, based on the battery data.

2. The method of claim 1, wherein the baseline charging protocol and the plurality of alternative charging protocols comprise: Charging is performed according to a corresponding current-voltage profile which sets the charging current according to the battery voltage.

3. The method of claim 2, wherein the baseline charging protocol and the plurality of alternative charging protocols comprise: The corresponding current-voltage profile is selected from a plurality of baseline current-voltage profiles according to the current battery temperature, each of the plurality of baseline current-voltage profiles being associated with a different corresponding battery temperature.

4. The method of claim 2, determining the plurality of alternative charging protocols further comprising: The current-voltage profile of the baseline charging protocol is modified.

5. The method of claim 4, modifying the current-voltage profile further comprising: The battery model is applied to determine a modified current-voltage profile that will result in a charging time that is within a predetermined threshold difference from a charging time produced by the current-voltage profile of the baseline charging protocol.

6. The method according to claim 5, applying the battery model further comprising: At least one internal state limit in the battery model is modified.

7. The method according to claim 1, wherein: a subset of the plurality of electric vehicles being configured to charge their batteries for a predetermined period of time in accordance with the plurality of alternative charging protocols; and The battery data is measured during or after a predetermined period of time. The method of claim 7 , wherein the predetermined period of time is at least one week.

9. The method of claim 1, wherein the battery data comprises at least one of: (i) battery current measurements, (ii) battery voltage measurements, (iii) battery temperature measurements, and (iv) battery state of charge measurements.

10. The method of claim 1, updating the baseline charging protocol further comprising: determining, based on the battery data, a modification to the baseline charging protocol that will result in at least one of: (i) slower battery aging and (ii) faster charging time compared to the baseline charging protocol; as well as The baseline charging protocol is updated according to the determined modifications.

11. The method of claim 10, determining a modification to the baseline charging protocol further comprising: identifying, based on the battery data, from the plurality of alternative charging protocols an alternative charging protocol that results in at least one of: (i) slower battery aging and (ii) faster charging time compared to the baseline charging protocol; as well as Modifications to the baseline charging protocol are determined based on the identified alternative charging protocol.

12. The method of claim 1, updating the baseline charging protocol further comprising: determining updated internal state limits for a battery model based on the battery data; as well as The baseline charging protocol is updated with updated internal state limits by applying the battery model.

13. The method of claim 1, updating the baseline charging protocol further comprising: determining a gradient based on the battery data; as well as The baseline charging protocol is updated based on the gradient.

14. The method according to claim 1, further comprising: Utilizing the transceiver, an updated baseline charging protocol is transmitted to the plurality of electric vehicles, the plurality of electric vehicles being configured to charge their batteries according to the updated baseline charging protocol.

15. The method according to claim 1, further comprising: A subset of the plurality of electric vehicles is selected, with the processor, from the plurality of electric vehicles.

16. The method of claim 15, selecting a subset of the plurality of electric vehicles further comprising: The subset of the plurality of electric vehicles is selected to be a random subset of the plurality of electric vehicles.

17. The method of claim 15, selecting a subset of the plurality of electric vehicles further comprising: The subset of the plurality of electric vehicles is selected based on at least one of: (i) environmental conditions, (ii) driving styles, and (iii) charging behaviors associated with the plurality of electric vehicles.

18. The method of claim 17, wherein the plurality of electric vehicles are configured to measure data comprising at least one of: (i) environmental condition data, (ii) driving style data, and (iii) charging behavior data, the method further comprising: The data is received from the plurality of electric vehicles using the transceiver.

19. The method of claim 15, wherein the method is periodically iterated to further update the baseline charging protocol, each iteration of the method comprising: selecting a new subset of the plurality of electric vehicles from the plurality of electric vehicles; and identifying new multiple alternative charging protocols.

20. A method for adapting a charging protocol for charging a battery of an electric vehicle, the method comprising: Using a transceiver of the battery management system, receiving an alternative charging protocol from a server; controlling, using a processor of the battery management system, charging of the battery according to the alternative charging protocol; measuring battery data during or after charging the battery according to the alternative charging protocol using at least one sensor of the battery management system; utilizing the transceiver to transmit the battery data to the server; as well as With the transceiver, an updated baseline charging protocol is received, the updated baseline charging protocol having been determined based on the battery data and further battery data from a further electric vehicle.

Images