Automatic management system for dual-design battery pack

Abstract

A system for managing an energy storage device in an electric vehicle includes a battery pack having an energy module and a power module connected in parallel with the energy module. The energy module is adapted to generate a first current. At least one DC-DC (direct current to direct current) converter is adapted to receive a first current from the energy module and to transfer a current referred to herein as a "DC-DC current" to the power module. The system includes a controller having a processor and tangible non-transitory memory on which instructions are recorded for automatically managing a set of parameters associated with a battery pack under a plurality of constraints. The power module is adapted to deliver a second current for powering a load in the electric vehicle. Operation of the electric vehicle is controlled based in part on the set of parameters.

Description

[0001] introduce

[0002] The present disclosure generally relates to the management of energy storage devices in vehicles. More specifically, the present disclosure relates to systems and methods for the automatic management of dual design battery packs. The use of mobile platforms that employ rechargeable energy sources (both as proprietary energy sources and as non-proprietary energy sources) has greatly increased in the past few years. Energy storage devices with battery packs can store and release electrochemical energy as needed during a given operating mode. The electrochemical energy can be used for propulsion, heating or cooling the cabin, powering vehicle accessories, and other purposes. The individual battery cells in the battery pack can be characterized by different states of charge, power, and capacity rates. In a battery pack with complex structures, the management of various parameters can be challenging. Summary of the invention

[0003] Disclosed herein is a system for managing an energy storage device in an electric vehicle. The system includes a battery pack having an energy module and a power module connected in parallel with the energy module. The energy module is adapted to generate a first current. At least one DC-DC (direct current to direct current) converter is adapted to receive a first current from the energy module and transmit a current referred to herein as a "DC-DC current" to the power module. The system includes a controller having a processor and a tangible non-transitory memory, on which instructions are recorded for automatically managing a set of parameters associated with the battery pack under multiple constraints.

[0004] The power module is adapted to deliver a second current for powering a load in the electric vehicle. The energy module is adapted to selectively recharge the power module with the charging current after a predefined event of relatively high power demand. The parameter set includes the DC-DC current, a first state of charge defined by the energy module, and a second state of charge defined by the power module. Operation of the electric vehicle is controlled based in part on the parameter set.

[0005] The energy module and the power module may have different chemistries. In one embodiment, the energy module includes corresponding battery cells composed of nickel, cobalt oxide and manganese. The power module may include corresponding battery cells composed of lithium, iron and phosphate. The electric vehicle may be adapted to undergo a first phase and a second phase. The first phase is associated with an initial acceleration mode and / or take-off mode of the vehicle, while the second phase is associated with a driving mode and / or a cruising mode of the vehicle. The energy module may be adapted to recharge the power module during the second phase, so that the energy module is the sole source of power for the electric vehicle during the second phase.

[0006] The plurality of constraints may include:

[0007] (1 / n)[IC(t)-I I，MAX ]<I DC (t)<(1 / n)[I C (t)-I I，MIN (t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current, respectively. The plurality of constraints may include:

[0008] [V2(t) / (n*V1(t))] [I 2，MIN -I L (t)]≤I DC (t)[V2(t) / (n*V1(t))] [I 2，MAX -I L (t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, V1 and V2 are the voltages of the energy module and the power module respectively, I L is the load current delivered to the load in the vehicle, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current respectively.

[0009] The plurality of constraints may include: C (t)<I 1，MAX , where I C is the charging current, and I 1,MAX is the maximum value of the first current. The plurality of constraints may include: ΔI C (t)≤D, where ΔI DC is the incremental change of the DC-DC current over time, and D is a predefined threshold. In one embodiment, the predetermined threshold is approximately 1 ampere. The DC-DC current may be between approximately 10 amperes and 100 amperes.

[0010] Disclosed herein is a method for managing an energy storage device in an electric vehicle having a controller, the controller having a processor and a tangible non-transitory memory, the energy storage device having a battery pack. The method includes incorporating an energy module and a power module into the battery pack. The energy module and the power module are connected in parallel. A first current is generated via the energy module. The method includes adapting at least one DC-DC converter to receive a first current from the energy module and transmitting the DC-DC current to the power module. The method includes managing a set of parameters related to the battery pack via a controller, and subjecting the set of parameters to multiple constraints. The power module is adapted to deliver a load current for powering a load in the vehicle. The method includes adapting the energy module to selectively recharge the power module with a charging current after a predefined event of relatively high power demand. The operation of the electric vehicle is controlled based in part on the set of parameters, the set of parameters including a DC-DC current, a charging current, a first state of charge defined by the energy module, and a second state of charge defined by the power module.

[0011] Disclosed herein is an electric vehicle having a battery pack, the battery pack having an energy module adapted to generate a first current and a power module connected in parallel with the energy module. At least one DC-DC converter is adapted to receive the first current from the energy module and transmit the DC-DC current to the power module. The electric vehicle includes a controller having a processor and a tangible non-transitory memory, and instructions are recorded on the tangible non-transitory memory for automatically managing a set of parameters related to the battery pack under multiple constraints. The power module is adapted to deliver a second current for powering a load in the vehicle, and the energy module is adapted to selectively recharge the power module with a charging current after a predefined event of relatively high power demand. The parameter set includes a DC-DC current, a first state of charge defined by the energy module, and a second state of charge defined by the power module, and the operation of the electric vehicle is controlled in part based on the parameter set.

[0012] A first aspect of the present disclosure provides a system for managing an energy storage device in an electric vehicle, the system comprising:

[0013] A battery pack having an energy module adapted to generate a first current and a power module connected in parallel with the energy module;

[0014] at least one DC-DC (Direct Current to Direct Current) converter adapted to receive a first current from the energy module and transmit a DC-DC (Direct Current to Direct Current) current to the power module;

[0015] a controller having a processor and a tangible non-transitory memory on which instructions are recorded for automatically managing a set of parameters associated with the battery pack under a plurality of constraints;

[0016] wherein the power module is adapted to deliver a second current, the energy module is adapted to selectively recharge the power module with the charging current after a predefined event of relatively high power demand, and

[0017] The parameter set includes the DC-DC current, the charging current, a first charging state defined by the energy module, and a second charging state defined by the power module, and the operation of the electric vehicle is controlled based in part on the parameter set.

[0018] According to the system of the first aspect of the present disclosure, the energy module and the power module have different chemical properties.

[0019] The system according to the first aspect of the present disclosure, wherein:

[0020] The energy module includes respective battery cells composed of nickel, cobalt oxide and manganese; and

[0021] The power module includes corresponding battery cells composed of lithium, iron and phosphate.

[0022] The system according to the first aspect of the present disclosure, wherein:

[0023] The electric vehicle is adapted to undergo a first phase associated with an initial acceleration mode and / or a take-off mode of the vehicle and a second phase associated with a driving mode and / or a cruising mode of the vehicle; and

[0024] The energy module is adapted to recharge the power module during the second phase, such that the energy module is the sole source of electrical power for the electric vehicle during the second phase.

[0025] According to the system of the first aspect of the present disclosure, the plurality of constraints include: (l / n)[I C (t)-I l，MAX ]≤I DC (t)≤(l / n)[I C (t)-I l，MIN (t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current respectively.

[0026] According to the system of the first aspect of the present disclosure, the plurality of constraints include: [V2(t) / (n*V1(t))][I 2，MIN -I L (t)]≤I DC (t)[V2(t) / (n*V1(t))][I 2，MAX -IL(t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, V1 and V2 are the voltages of the energy module and the power module respectively, I L is the load current transmitted to the load in the vehicle, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current respectively.

[0027] According to the system of the first aspect of the present disclosure, the plurality of constraints include: C (t)≤I 1，MAX , where I C is the charging current, and I 1,MAX is the maximum value of the first current.

[0028] According to the system of the first aspect of the present disclosure, the plurality of constraints include: ΔI C (t)<D, where ΔI DC is the incremental change of the DC-DC current over time, and D is a predefined threshold value.

[0029] According to the system of the first aspect of the present disclosure, the predetermined threshold is approximately 1 ampere.

[0030] According to the system of the first aspect of the present disclosure, the DC-DC current is between about 10 amps and 100 amps.

[0031] A second aspect of the present disclosure provides a method for managing an energy storage device in an electric vehicle having a controller, the controller having a processor and a tangible non-transitory memory, the energy storage device having a battery pack, the method comprising:

[0032] Incorporating an energy module and a power module into the battery pack, wherein the energy module and the power module are connected in parallel;

[0033] generating a first current via the energy module;

[0034] at least one DC-DC (direct current to direct current) converter adapted to receive a first current from the energy module and transmit a DC-DC (direct current to direct current) current to the power module;

[0035] managing, via the controller, a set of parameters associated with the battery pack and subjecting the set of parameters to a plurality of constraints;

[0036] adapting the power module to deliver a load current for powering a load in the vehicle;

[0037] adapting the energy module to selectively recharge the power module with a charging current after a predefined event of relatively high power demand; and

[0038] Operation of the electric vehicle is controlled based in part on the set of parameters, the set of parameters including a DC-DC current, a charging current, a first state of charge defined by the energy module, and a second state of charge defined by the power module.

[0039] The method according to the second aspect of the present disclosure further includes:

[0040] incorporating corresponding battery cells composed of nickel, cobalt oxide and manganese into the energy module; and

[0041] Corresponding battery cells consisting of lithium, iron and phosphate are incorporated into the power module.

[0042] The method according to the second aspect of the present disclosure further includes:

[0043] The plurality of constraints are set to include:

[0044] (1 / n)[I C (t)-I 1，MAX ]I DC (t)(1 / n)[I C (t)-I 1，MIN (t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current respectively.

[0045] The method according to the second aspect of the present disclosure further includes:

[0046] The plurality of constraints are set to include:

[0047] [V2(t) / (n*V1(t))}[I 2，MIN -I L (t)]<I DC (t)[V2(t) / (n*V1(t)][I 2，MAX -I L (t)], where t is time, IDC is the DC-DC current, n is the number of phases of the DC-DC current, V1 and V2 are the voltages of the energy module and the power module respectively, I L is the load current transmitted to the load in the electric vehicle, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current respectively.

[0048] A third aspect of the present disclosure provides an electric vehicle, comprising:

[0049] A battery pack having an energy module adapted to generate a first current and a power module connected in parallel with the energy module;

[0050] at least one DC-DC (Direct Current to Direct Current) converter adapted to receive a first current from the energy module and transmit a DC-DC (Direct Current to Direct Current) current to the power module;

[0051] a controller having a processor and a tangible non-transitory memory on which instructions are recorded for automatically managing a set of parameters associated with the battery pack under a plurality of constraints;

[0052] wherein the power module is adapted to deliver a second current for powering a load in the vehicle, the energy module being adapted to selectively recharge the power module with a charging current after a predefined event of relatively high power demand; and

[0053] The parameter set includes a DC-DC current, a first state of charge defined by the energy module, and a second state of charge defined by the power module, and the operation of the electric vehicle is controlled based in part on the parameter set.

[0054] The electric vehicle described in the third aspect of the present disclosure, wherein the energy module and the power module have different chemical properties.

[0055] The electric vehicle according to the third aspect of the present disclosure, wherein:

[0056] The energy module includes respective battery cells composed of nickel, cobalt oxide and manganese; and

[0057] The power module includes corresponding battery cells composed of lithium, iron and phosphate.

[0058] The electric vehicle according to the third aspect of the present disclosure, wherein the plurality of constraints include: (l / n) [I C (t)-I l，MAX ]≤I DC (t)≤(l / n)[I C (t)-Il，MIN (t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current respectively.

[0059] The electric vehicle according to the third aspect of the present disclosure, wherein the plurality of constraints include: [V2(t) / (n*V1(t))][I 2，MIN -I L (t)]≤I DC (t)[V2(t) / (n*V1(t))][I 2，MAX -IL(t)], where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, V1 is the corresponding voltage of the energy module, V1 and V2 are the voltages of the energy module and the power module respectively, I L is the load current transmitted to the load in the vehicle, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current respectively.

[0060] The electric vehicle according to the third aspect of the present disclosure, wherein the plurality of constraints include: C (t)≤I 1，MAX , where I C is the charging current, and I 1,MAX is the maximum value of the first current.

[0061] The above features and advantages and other features and advantages of the present disclosure are readily apparent from the following detailed description of the best modes for carrying out the disclosure when taken in connection with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a schematic diagram of a system for managing an energy storage device, the system having a controller;

[0063] Figure 2 It can be Figure 1 A schematic diagram of an example modular architecture employed by a system;

[0064] Figure 3 It can be Figure 1 A schematic flow chart of a method performed by a controller; and

[0065] Figure 4A , 4B4C and 4D are schematic example graphs illustrating, respectively, current, state of charge, voltage, and current delivered by a DC-DC (direct current to direct current) converter of an example energy storage device over time.

[0066] Representative embodiments of the present disclosure are shown in the accompanying drawings by way of non-limiting examples and are described in more detail below. However, it should be understood that the novel aspects of the present disclosure are not limited to the specific forms illustrated in the drawings listed above. On the contrary, the present disclosure encompasses modifications, equivalents, combinations, sub-combinations, arrangements, groupings, and substitutions that fall within the scope of the present disclosure, such as those covered by the appended claims. DETAILED DESCRIPTION

[0067] Referring to the drawings, wherein like reference numerals refer to like parts. Figure 1 is a schematic diagram illustrating a system 10 for managing an energy storage device 12. Figure 1 , the energy storage device 12 can be part of an electric vehicle 20. The electric vehicle 20 can be partially electric or fully electric. The electric vehicle 20 can be a mobile platform such as, but not limited to, a passenger car, a sport utility vehicle, a light truck, a heavy vehicle, an ATV, a minivan, a bus, a transport vehicle, a bicycle, a mobile robot, an agricultural implement (e.g., a tractor), sports-related equipment (e.g., a golf cart), a boat, an airplane, and a train. It should be understood that the electric vehicle 20 can take many different forms and have additional components.

[0068] For illustration purposes, Figure 1 The energy storage device 12 in FIG. 1 is schematically presented as a hydraulic system. However, it should be understood that the energy storage device 12 is a battery system having a battery pack 14. The battery pack 14 is characterized in that it employs a "dual design" system of both energy battery cells and power battery cells. Figure 2 is a schematic diagram of an example modular architecture 100 that may be employed by the system 10. Figure 1-2 , the battery pack 14 includes corresponding battery cells 18 arranged in an energy module 22 and a power module 24. The power module 24 is connected in parallel with the energy module 22. The power module 24 supplies more power than the energy module 22. The energy module 22 supplies constant power for a longer duration than the power module 24. The number of corresponding battery cells 18 in the energy module 22 and the power module 24 may vary based on the current application.

[0069] The design and / or composition of power module 24 allows ions to move quickly into and out of the electrodes, thereby generating a higher power output. The design and / or composition of energy module 22 reduces the movement of ions into and out of the electrodes, thereby limiting the power output. In other words, compared to power module 24, energy module 22 is adapted to provide continuous current for a longer period of time, and compared to energy module 22, power module 24 can provide a higher current for a short duration.

[0070] In one embodiment, the corresponding battery cells 18 in the power module include electrodes formed of a porous material and a thinner coating, while the corresponding battery cells 18 in the energy module include electrodes formed of a denser material and a thicker coating. In one embodiment, the voltage of the energy module 22 is about 800 volts (V), and the voltage of the power module 24 is between about 400V and 600V.

[0071] In one embodiment, the energy module 22 and the power module 24 use batteries based on different chemistries. For example, the energy module 22 may include a battery cell having a cathode material composed of nickel, cobalt oxide, and manganese. The power module 24 may include a battery cell having a cathode material composed of lithium, iron, and phosphate. It should be understood that the system 10 is independent of the specific battery cell type, chemistry, and configuration of the battery pack 14. In another embodiment, the energy module 22 and the power module 24 use different battery designs with the same chemistry.

[0072] Reference Figure 1 The system 10 includes a controller C having at least one processor P and at least one memory M (or a non-transitory tangible computer-readable storage medium), and recording instructions for executing the method 200 for managing the battery pack 14 on the memory M, as described below with reference to Figure 3 The method 200 is described. The memory M may store an executable instruction set, and the processor P may execute the instruction set stored in the memory M. The method 200 enables automatic management of a set of parameters associated with the battery pack 14 under a plurality of constraints.

[0073] Reference Figure 1-2 , the energy module 22 is adapted to generate a first current 110. The energy storage device 12 includes at least one direct current to direct current (DC-DC) converter 26, the DC-DC converter 26 is adapted to receive the first current 110 from the energy module 22 (see Figure 2 The DC-DC converter 26 is adapted to transmit a current, referred to herein as a DC-DC (direct current-to-direct current) current 112 , to the power module 24 . The power module 24 is adapted to deliver a second current 114 .

[0074] Reference Figure 1-2, the power module 24 is adapted to provide on-demand power (via the traction inverter 28) for powering a load such as a motor 30 in the electric vehicle 20. The traction inverter 28 converts DC power from the battery pack 14 to an AC output for operating the motor 30. When the electric vehicle 20 is operating, the battery pack 14 is controlled by the controller C to (ultimately) generate motor torque and deliver it to the wheels 32, and thus propel the electric vehicle 20.

[0075] Controller C implements a control strategy that uses the DC-DC converter 26 to maintain a full charge of the power module 24 after a relatively high power demand event. In other words, the power module 24 is recharged after each relatively high power demand event so that the power module 23 can meet the needs of the vehicle 20 when the next such event occurs. The relatively high power demand event can vary based on the current application. In one example, the predefined event is the initial acceleration and / or takeoff of the electric vehicle 20. The predefined event can include the vehicle 20 being in towing mode and towing or hauling a load. As described below, controller C manages the individual energy from the power module 24 and the energy module 22 to meet the power demand while meeting strict constraints in real time, thereby increasing the life of the battery pack 14 and the DC-DC converter 26.

[0076] The maximum and minimum currents that can be drawn from the power module 24 and energy module 22 , respectively, vary over time as their respective states of charge transition. Figure 1 The charging states of the power module 24 and the energy module 22 are schematically indicated as liquid levels L1 and L2, respectively. The liquid levels L1 and L2 of the power module 24 and the energy module 22 should neither be overfilled nor empty. Figure 1 , the maximum current delivered by the energy module 22 to the DC-DC converter 26 can be limited by the first conduit 34. The user can limit the current entering the power module 24 via the selector 36. Similarly, the maximum current delivered by the power module 24 to the traction inverter 28 can be limited by the second conduit 38.

[0077] Reference Figure 2 , the battery pack 14 can be selectively recharged via a DC fast charging voltage from an off-board DC fast charging station (DCFC) 140. The desired charging current 142 [I C (t)] can be transmitted to the energy module based on the input from the energy module observer 130. The energy module 22 and the power module 24 can be operated simultaneously. The DC-DC current is used to modulate the current from the energy module 22 and the power module 24 while meeting the load. The direction and amplitude of the second current 114 from the power module 24 vary with time. As shown below with respect to Figure 4AAs depicted, in phases 300 and 304 , the power module 24 is outputting current (discharging), while in phase 302 the power module 24 is charging.

[0078] Now refer to Figure 3 , showing the storage Figure 1 Flow chart of method 200 on controller C and executable by controller C. Method 200 may be embodied as stored in Figure 1 on the controller C and can be Figure 1 The method 200 need not be applied in the specific order described herein. In addition, it should be understood that some steps may be eliminated. The method 200 may be performed dynamically.

[0079] according to Figure 3 At block 202, method 200 includes obtaining input data. Figure 2 The modular architecture 100 may include a prediction model 120 that receives inputs from an input module 122 , such as a desired state of charge of the power module 24 . The prediction model 120 may receive data from a constraint module 124 , including a current throttle requirement 126 .

[0080] Proceeding to block 204, the controller C (via the predictive model 120) is adapted to receive input from an energy module observer (EMO) module 130, which transmits the voltage (Vl) and state of charge (SOC1) of the energy module 22 (given by Figure 2 132 in the figure). Proceeding to block 206, the controller C is programmed (via the predictive model 120) to receive input from a power module observer (PMO) module 134, which transmits the voltage (V2) and state of charge (SOC2) of the power module 24 (indicated by Figure 2 , as indicated by signal 136 in ).

[0081] Proceeding to block 208, the controller C (via execution of the prediction model 120) is adapted to calculate a desired DC-DC current 150 (I DC ). For the desired DC-DC current 150 (I DC ) include:

[0082] (1 / n)[I C (t)-I 1，MAX ]≤I DC (t)≤(1 / m)[I C (t)-I 1，MIN (t)]

[0083] Here t is the time, IDC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current 142, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current 110, respectively. DC ) include:

[0084] [V2(t) / (n*V1(t))][I 2，MIN -I L (t)]≤I DC (t)≤[V2(t)*(n*V1(t))][I 2，MAX -IL(t)].

[0085] Here t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, V1 and V2 are the voltages of the energy module 22 and the power module 24, respectively, I L is the load current transmitted to the load 30 in the vehicle 20, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current 114 , respectively.

[0086] The constraints include: C (t)≤I 1，MAX , where I C is the charging current 142, and I 1,MAX is the maximum value of the first current 110. The constraint may also include: ΔIC(t)≤D, where ΔI DC is the incremental change in the desired DC-DC current 150 over time, and D is a predefined threshold. In one example, the predefined threshold is approximately 1 ampere.

[0087] Proceeding to block 210, the controller C is programmed to employ closed-loop feedback to minimize the difference (as shown at node 154) between the desired DC-DC current 150 (calculated in block 208) and the actual DC-DC current (signal 152), which is delivered by the DC-DC converter 26. A closed-loop control module available to those skilled in the art may be employed. Proceeding to block 212, the operation of the vehicle 20 is controlled based on the set of parameters of the battery pack 14. Controlling the operation of the vehicle 20 includes satisfying the torque demand of the vehicle 20 through the battery pack 14 while satisfying strict constraints in real time.

[0088] Reference now FIG. 4A to FIG. 4D, shows a schematic example diagram of an example electric vehicle 20. In this example, the electric vehicle 20 is an aircraft that uses power from the energy storage device 12 via a rotor (not shown) for vertical takeoff, cruise, and vertical landing.

[0089] exist Figure 4A , 4B , 4C and 4D, the horizontal axis T indicates time. Figures 4A to 4D The time period shown in FIG. 3 is subdivided into a first phase 300, a second phase 302, and a third phase 304. The first phase 300 is associated with a time period of an initial acceleration mode and / or a take-off mode of the electric vehicle 20. The second phase 302 is associated with a driving mode and / or a cruising mode of the electric vehicle 20. The third phase 304 is associated with a landing mode or deceleration of the electric vehicle 20. The energy module 22 can be adapted to selectively recharge the power module 24 during the second phase 302, so that the energy module 22 is the only power source for the battery pack 14 during the second phase 302.

[0090] Reference Figure 4A , the vertical axis Y1 shows the current (in amperes) and the horizontal axis shows the time T. Trace 310 shows the second current 114, while trace 320 shows the load current (I L ). Traces 330 and 340 are horizontal lines showing the minimum and maximum values ​​of the second current 114 (I 2,MIN and I 2,MAX ). Load current (I L ) increases in stages 300 and 304. In stages 300 and 304, the power module 24 outputs current (discharges), while in stage 302 the power module 24 is charging. Figure 4A In the diagram, negative current indicates discharge, while positive current indicates charge.

[0091] Reference Figure 4B , the vertical axis Y2 indicates the state of charge, and the horizontal axis shows time T. Trace 350 shows the state of charge (SOC1) of the energy module 22, and trace 355 shows the state of charge (SOC2) of the power module 24. Figure 4B As shown by trace 355 in FIG. 3 , the state of charge (SOC1) of the energy module continues to decrease during each of the first, second, and third stages 300, 302, 304. As shown by trace 350, the state of charge (SOC2) of the power module is shown to decrease sharply in the first stage 300, then increase during the second stage 302 as it is charged by the energy module 22, and finally decrease sharply in the third stage 304 when both the energy module 22 and the power module 24 are supplying power to the load 30.

[0092] Reference Figure 4C, the vertical axis Y3 indicates voltage, and the horizontal axis shows time T. Trace 360 ​​shows the voltage (V1) of the energy module 22, and trace 365 shows the voltage (V2) of the power module 24. As shown by traces 360, 365, the corresponding voltages V1, V2 are relatively constant during the second stage 302, and show a slight decrease during the first stage 300 and the third stage 304, the difference is due to the smaller capacity.

[0093] Reference Figure 4D , the vertical axis Y4 indicates the DC-DC current, and the horizontal axis shows the time T. Traces 370, 380, 390 respectively show the DC-DC current, the predefined minimum DC-DC current, and the predefined maximum DC-DC current. The minimum and maximum DC-DC currents can be adjusted to obtain the best results. As shown in trace 370, the DC-DC current shows a sharp increase during the first stage 300, is relatively constant during the second stage 302, and shows a decrease just before the third stage 304.

[0094] Reference Figure 1 , the controller C may be configured to receive and transmit wireless communications with a cloud unit 52 via a wireless network 50. The cloud unit 52 may include one or more servers hosted on the Internet for storing, managing, and processing data. Figure 1 The wireless network 50 may be a wireless local area network (LAN), a wireless metropolitan area network (MAN), a wireless wide area network (WAN), WIFI or Bluetooth. TM connect.

[0095] In summary, the system 10 allows for the generation of real-time constraints for current limits of the energy module 22 and the power module 24 using battery models and predictions. The corresponding battery cells 18 in the energy module 22 typically deliver a sustained and continuous current over a long duration, while the corresponding battery cells 18 in the power module 24 typically deliver a high current load at intermittent intervals over a short duration. The system 10 allows for selective adjustment of the charge level of the power module 24. The DC-DC converter 26 allows the energy module 22 to charge the power module 24.

[0096] As used herein, the terms "dynamic" and "dynamically" describe steps or processes that are performed in real time and are characterized by monitoring or otherwise determining the state of a parameter and regularly or periodically updating the state of the parameter during execution of a routine or between execution iterations of a routine.

[0097] Figure 1 The controller C may be an integral part of other controllers of the electric vehicle 20 , or a separate module operably connected to the other controllers of the electric vehicle 20 . Figure 1The controller C may include: a computer-readable medium (also referred to as a processor-readable medium), including a non-transitory (e.g., tangible) medium that participates in providing data (instructions) that can be read by a computer (e.g., by a processor of a computer). Such media may take a variety of forms, including but not limited to non-volatile media and volatile media. Non-volatile media may include, for example, optical or magnetic disks and other persistent memories. Volatile media may include, for example, dynamic random access memory (DRAM), which may constitute a main memory. Such instructions may be transmitted via one or more transmission media (including coaxial cables, copper wires, and optical fibers, including wires that constitute a system bus coupled to a processor of a computer). Some forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, other magnetic media, CD-ROMs, DVDs, other optical media, physical media with hole patterns, RAMs, PROMs, EPROMs, FLASH-EEPROMs, other memory chips or cassettes, or other media that a computer can read.

[0098] The lookup table, database, data repository or other data storage device described herein may include various mechanisms for storing, accessing and retrieving various data, including hierarchical databases, a set of files in a file system, an application database in a proprietary format, a relational database system (RDBMS), etc. Each such data storage device may be included in a computing device that uses a computer operating system (such as one of those mentioned above) and may be accessed via a network in one or more of various ways. The file system may be accessed from a computer operating system and may include files stored in various formats. In addition to the language (such as the PL / SQL language mentioned above) for creating, storing, editing and executing stored procedures, RDBMS may also use structured query language (SQL).

[0099] The flowcharts shown in (one or more) figures illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, segment or part of the code, and the module, segment or part of the code includes one or more executable instructions for implementing (one or more) specified logical functions. It should also be noted that each box in the block diagram and / or flowchart illustration and the combination of boxes in the block diagram and / or flowchart illustration can be implemented by a system based on special purpose hardware or a combination of special purpose hardware and computer instructions that perform specified functions or actions. These computer program instructions can also be stored in a computer-readable medium, which can instruct a controller or other programmable data processing device to operate in a specific manner so that the instructions stored in the computer-readable medium produce an article of manufacture, which includes instructions for implementing the functions / actions specified in the flowchart and / or block diagram box.

[0100] The numerical values ​​of parameters (e.g., quantities or conditions) in this specification (including the appended claims) should be understood as being modified by the term "approximately" in each corresponding instance, regardless of whether "approximately" actually appears before the numerical value. "Approximately" means that the numerical value recorded allows some slight imprecision (having a certain approximation to the exact value; approximately or moderately close to the value; almost). If the imprecision provided by "approximately" is not otherwise understood in the field with its ordinary meaning, the "approximately" used herein at least represents the changes that may be caused by the ordinary methods of measuring and using such parameters. In addition, the disclosure of the range includes the disclosure of each value and the further subdivided range within the entire range. Thus, each value within the range and the endpoints of the range are disclosed as separate embodiments.

[0101] The detailed description and the drawings or individual figures are supportive and descriptive of the present disclosure, but the scope of the present disclosure is limited only by the claims. Although some best modes and other embodiments for implementing the claimed disclosure have been described in detail, there are various alternative designs and embodiments for practicing the disclosure defined in the appended claims. In addition, the embodiments shown in the drawings or the features of the individual embodiments mentioned in this description are not necessarily to be understood as embodiments independent of each other. On the contrary, it is possible that each feature described in one of the examples of the embodiments can be combined with one or more other desired features from other embodiments, thereby obtaining other embodiments that are not described in words or with reference to the drawings. Therefore, such other embodiments fall within the framework of the scope of the appended claims.

Claims

1. A system for managing an energy storage device in an electric vehicle, the system comprising: A battery pack having an energy module adapted to generate a first current and a power module connected in parallel with the energy module; at least one DC-DC (Direct Current to Direct Current) converter adapted to receive a first current from the energy module and transmit a DC-DC (Direct Current to Direct Current) current to the power module; a controller having a processor and a tangible non-transitory memory on which instructions are recorded for automatically managing a set of parameters associated with the battery pack under a plurality of constraints; wherein the power module is adapted to deliver a second current, the energy module is adapted to selectively recharge the power module with the charging current after a predefined event of relatively high power demand, and The parameter set includes the DC-DC current, the charging current, a first charging state defined by the energy module, and a second charging state defined by the power module, and the operation of the electric vehicle is controlled based in part on the parameter set.

2. The system of claim 1, wherein the energy module and the power module have different chemistries.

3. The system of claim 2, wherein: The energy module includes respective battery cells composed of nickel, cobalt oxide and manganese; and The power module includes corresponding battery cells composed of lithium, iron and phosphate.

4. The system of claim 2, wherein: The electric vehicle is adapted to undergo a first phase associated with an initial acceleration mode and / or a take-off mode of the vehicle and a second phase associated with a driving mode and / or a cruising mode of the vehicle; and The energy module is adapted to recharge the power module during the second phase, such that the energy module is the sole source of electrical power for the electric vehicle during the second phase.

5. The system of claim 1, wherein the plurality of constraints comprises: (1 / n)[I C (t)-I 1，MAX ]≤I DC (t)≤(1 / n)[I C (f)-I 1，MIN (f)], where t is the time valve, I DC is the DC-DC current, n is the number of phases of the DC-DC current, I C is the charging current, and I 1,MIN and I 1,MAX are the minimum and maximum values ​​of the first current respectively.

6. The system of claim 1, wherein the plurality of constraints comprises: [V2(f) / (n*V1(t))][I 2，MIN -I L (t)]≤I DC (t)≤[V2(t) / (n*V1(t))][I 2，MAX -I L (t)], Where t is time, I DC is the DC-DC current, n is the number of phases of the DC-DC current, V1 and V2 are the voltages of the energy module and the power module respectively, I L is the load current transmitted to the load in the vehicle, and I 2,MIN and I 2,MAX are the minimum and maximum values ​​of the second current respectively.

7. The system of claim 6, wherein the plurality of constraints comprises: I C (t)≤I 1，MAX , where I C is the charging current, and I 1,MAX is the maximum value of the first current.

8. The system of claim 7, wherein the plurality of constraints comprises: ΔI C (t)≤D, where ΔI DC is the incremental change of the DC-DC current over time, and D is a predefined threshold value.

9. The system of claim 8, wherein the predetermined threshold is approximately 1 ampere.

10. The system of claim 1, wherein the DC-DC current is between approximately 10 amps and 100 amps.

Images