METHOD AND DEVICE FOR CONTROLLING ELECTRIC MACHINES

Abstract

A control unit (2) for controlling the operation of at least one first and one second traction machine (7, 10) in a vehicle (1), wherein the control unit (2) comprises a processor configured to: predict an operating temperature (PT1, PT2) of each of the at least first and second traction machines (7, 10) for at least part of a current route; determine at least first and second torque requirements (DS1, DS2) for the at least first and second traction machines (7, 10), wherein the at least first and second torque requirements (DS1, DS2) are determined as a function of the predicted operating temperatures (PT1, PT2) of the at least first and second traction machines (7, 10); generate at least first and second traction motor control signals (DSF1, DSF2) as a function of the determined at least first and second torque requirements (DS1, DS2); and generate at least first and second power loss deductions (PP1,PP2) depending on the predicted operating temperatures (PTA, PT2) of the at least first and second traction machine (7, 10), wherein the processor is configured to determine a first predicted time at which the operating temperature of the first traction machine (7) is expected to exceed a first temperature threshold (TTH1), and to apply the first power loss deduction (PP1) a predetermined first time interval before the first predicted time, wherein the duration of the first time interval is proportional to the predicted operating temperature (PT1) and / or a predicted rate of change of the operating temperature (PT1) of the first traction machine (7).

Description

AREA OF INVENTION

[0001] This disclosure relates to a method and a device for controlling electrical machines. In particular, but not exclusively, this disclosure relates to a method and a device for controlling the torque distribution between several electrical machines. The method and the device have a particular application in a vehicle for controlling the torque distribution between traction motors. Aspects of the invention relate to a control system for controlling at least one first and one second traction machine, to a vehicle with a control system, to a method for controlling at least one first and one second traction machine, and to a non-transient, computer-readable medium. STATE OF THE ART

[0002] Equipping a battery electric vehicle (BEV) with more than one electric traction motor to transmit torque to one or more axles is a known practice. For example, the vehicle might consist of a first electric motor for transmitting torque to a front axle and a second electric motor for transmitting torque to a rear axle. This design offers various advantages in terms of performance, stability / traction, increased regenerative braking, and improved overall efficiency. Distributing torque between the two axles is a complex task that often requires considering conflicting characteristics and limitations.

[0003] A vehicle energy management (VEM) system is available to control the operation of the systems in the battery electric vehicle (BEV). The VEM system aims to optimize the coordination and operation of various vehicle systems, such as: the drive system (traction system), cooling systems, the high-voltage battery cooling system (HV), and the heating, ventilation, and air conditioning (HVAC) system.

[0004] At least in certain embodiments, the current invention aims at efficient control of a vehicle powertrain. BRIEF SUMMARY OF THE INVENTION

[0005] Aspects of the present invention relate to a control system, a vehicle, a method and a non-transitory computer-readable medium, as claimed in the attached claims.

[0006] According to another aspect of the present invention, a control system for controlling the operation of at least one first and one second drive motor in a vehicle is provided, wherein the control system comprises a processor configured to: to predict the operating temperature of each of the at least first and second traction engines for at least part of a current route, to determine at least the first and second torque requirements for the at least first and second traction machine, wherein the at least first and second torque requirements are determined depending on the predicted operating temperatures of the at least first and second traction machine, and The control system generates at least first and second traction motor control signals depending on the specified torque requirements. At least in certain embodiments, the control system uses route-ahead information to predict the thermal behavior of the at least first and second traction motors. This provides the control system with situational awareness, allowing it, at least in certain embodiments, to dynamically adjust the control system to improve energy efficiency. The control system attempts to identify segments of the current route where the temperature of one or more of the at least first and second electric motors may rise above a predetermined threshold.By anticipating the predicted thermal behavior, the control system can, at least in certain embodiments, more efficiently control the operation of the first and second traction motors during at least part of the current journey.

[0007] At least in certain embodiments, the control system can detect one or more possibilities for changing the torque distribution between at least the first and second electric machines in order to compensate for the thermal load on the first and second electric machines. By detecting such a possibility early on, the control system can proactively increase the proportion of the total requested torque generated by one or more of the at least first and second electric machines, for example, to prevent the predicted operating temperature of one of the at least first and second electric machines from exceeding a temperature threshold.

[0008] The first and second traction machines can each consist of an electric machine. Each electric machine can be connected to an inverter, which in turn can be connected to a traction battery. The traction machines can each be integrated into an electric drive unit (EDU).

[0009] The first and second torque requirements can consist of a scalar, represented, for example, by a real number. These requirements can include positive (+ve) or negative (-ve) variables to indicate the direction in which the torque is to be applied.

[0010] Depending on the predicted operating temperatures of at least the first and second traction motors, the processor can be configured to determine at least the first and second power loss deductions.

[0011] The power loss deduction for at least the first and second traction motors can be proportional to the predicted operating temperature or rate of change of the operating temperature of the at least first and second traction motors. Alternatively, the power loss deduction for at least the first and second traction motors can be directly proportional to the predicted operating temperature or rate of change of the operating temperature of the at least first and second traction motors.

[0012] The processor can be designed to determine at least the first and second torque requirements depending on at least the first and second power loss deductions.

[0013] The processor can be configured to determine a first predicted time (or times) at which the operating temperature of the first traction machine is expected to exceed a first temperature threshold. The processor can be configured to increase or apply the first power loss deduction a predetermined first time interval before the first predicted time. The duration of this first time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first traction machine.

[0014] Alternatively or additionally, the processor can be configured to determine a first predicted geographic location (or locations) where the operating temperature of the first traction engine is expected to exceed a first temperature threshold. The processor can be configured to increase or apply the first power loss deduction a predetermined first time interval before the vehicle arrives at the first predicted geographic location or at a first distance before the first predicted geographic location along the current route. The length of the first distance can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first traction engine.

[0015] The processor can be configured to determine a second predicted time at which the operating temperature of the second traction machine is expected to exceed a second temperature threshold. The processor can be configured to increase the second power loss deduction for a predetermined second time interval before the second predicted time. The duration of this second time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second traction machine.

[0016] Alternatively or additionally, the processor can be configured to determine a second predicted geographic location (or a plurality of second predicted geographic locations) where the operating temperature of the second traction engine is expected to exceed a second temperature threshold. The processor can be configured to increase or apply the second power loss deduction a predetermined second time interval before the vehicle arrives at the second predicted geographic location, or at a second distance before the second predicted geographic location along the current route. The length of the second distance can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second traction engine.

[0017] In at least certain embodiments, the processor can be configured to determine a first power loss deduction based on a predicted operating temperature of the first traction machine and / or a second power loss deduction based on a second predicted operating temperature of the second traction machine. The processor can be configured to determine a first predicted time at which the operating temperature of the first traction machine is expected to exceed a first temperature threshold. The processor can apply the first power loss deduction a predetermined first time interval before the first predicted time. The duration of this first time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first traction machine.Alternatively or additionally, the processor can be configured to determine a second predicted time at which the operating temperature of the second traction machine is expected to exceed a second temperature threshold. The processor can apply the second power loss deduction a predetermined second time interval before the second predicted time. The duration of the second time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second traction machine.

[0018] The notes contained in this document regarding the determination of a first power loss deduction with respect to a predicted operating temperature of the first traction machine can also apply to a predicted temperature of a first electric drive unit (EDU) that includes or consists of a first inverter for the first traction machine. The processor can be configured to determine a first power loss deduction as a function of a predicted operating temperature of the first EDU. The notes contained in this document regarding the determination of a second power loss deduction with respect to a predicted operating temperature of the second traction machine can also apply to a predicted temperature of a second electric drive unit (EDU) that includes or consists of a second inverter for the second traction machine.The processor can be configured to determine a second power loss deduction based on a predicted operating temperature of the second EDU. The processor can be configured to determine a first predicted time at which the operating temperature of the first EDU is expected to exceed a first temperature threshold. The processor can apply the first power loss deduction a predetermined first time interval before the first predicted time. The duration of the first time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first EDU. Alternatively or additionally, the processor can be configured to determine a second predicted time at which the operating temperature of the second EDU is expected to exceed a second temperature threshold.The processor can apply the second power loss deduction a predetermined second time interval before the second predicted time. The duration of the second time interval can be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second EDU.

[0019] The processor can be configured to predict the operating temperature of at least the first and second traction motors based on their expected load. The load of the first and second traction motors can be predicted based on one or more of the following: vehicle position data, vehicle speed, reference data on known geographical features, routes, speed limits, known or detected road conditions that might impose specific or special performance or load requirements, battery state of charge (SOC), external ambient air temperature or other climatic conditions, and estimated road load.

[0020] The processor can be configured to proactively control one or more vehicle cooling subsystems based on the predicted operating temperatures of the first and second traction motors. The processor can also be configured to actuate one or more vehicle cooling subsystems based on these predicted operating temperatures to provide cooling. The one or more vehicle cooling subsystems can consist of one or more of the following: a heat exchanger, such as a radiator, a cooling fan, a coolant pump, and an active aerodynamic air deflector.

[0021] The processor can be configured to predict vehicle stability, at least for part of a current route. The processor can determine at least the first and second torque demands based on the predicted vehicle stability.

[0022] According to a further aspect of the present invention, a control system for controlling the operation of at least one first and one second traction motor in a vehicle is provided, wherein the control system comprises a processor configured to predict vehicle stability for at least a portion of a current route. The processor can determine at least first and second torque requirements for the at least first and second traction motor. The at least first and second torque requirements can be determined based on the predicted vehicle stability. At least first and second traction motor control signals can be generated based on the determined at least first and second torque requirements.

[0023] Vehicle stability can be predicted depending on one or more of the following factors: a vehicle speed profile, a longitudinal acceleration profile, a lateral acceleration profile, and a coefficient of friction (µ).

[0024] According to another aspect of the present invention, a vehicle with a control system as described in this document is provided.

[0025] According to a further aspect of the present invention, a method for controlling the operation of at least one first and one second traction machine in a vehicle is provided, wherein the method comprises the following: Predictions of the operating temperature of each of the at least first and second traction motors for at least part of a current route, Determining at least first and second torque requirements for the at least first and second traction machine, wherein the at least first and second torque requirements are determined as a function of the predicted operating temperatures of the at least first and second traction machine, and Control of at least the first and second drive motor control signals depending on the specified at least first and second torque requirements.

[0026] The method may include determining at least one first and one second power loss deduction as a function of the predicted operating temperatures of the at least first and second traction motors. The at least first and second power loss deductions may be proportional to the predicted operating temperature or a predicted rate of change of the operating temperature of the at least first and second traction motors. Alternatively, the at least first and second power loss deductions may be directly proportional to the predicted operating temperature or a predicted rate of change of the operating temperature.

[0027] The procedure may include determining the at least first and second torque requirement depending on the at least first and second power loss deduction.

[0028] The method may include determining a first predicted time at which the operating temperature of the first traction machine is expected to exceed a first temperature threshold. The method may also include increasing the first power loss deduction over a predetermined first time interval prior to the first predicted time. The duration of this first time interval may be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first traction machine.

[0029] Alternatively or additionally, the method may include determining a first predicted geographic location (or a plurality of first predicted geographic locations) at which the operating temperature of the first traction engine is expected to exceed a first temperature threshold. The method may include increasing the first power loss deduction over a predetermined first time interval before the vehicle arrives at the first predicted geographic location or at a first distance before the first predicted geographic location along the current route. The length of the first distance may be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the first traction engine.

[0030] The method may include determining a second predicted time at which the operating temperature of the second traction engine is expected to exceed a second temperature threshold. The method may include increasing the second power loss deduction for a predetermined second time interval prior to the second predicted time. The duration of the second time interval may be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second traction engine.

[0031] Alternatively or additionally, the method may include determining a second predicted geographic location (or a plurality of second predicted geographic locations) at which the operating temperature of the second traction engine is expected to exceed a second temperature threshold. The method may include increasing the second power loss deduction over a predetermined second time interval before the vehicle arrives at the second predicted geographic location or at a second distance from the second predicted geographic location along the current route. The length of the second distance may be proportional to the predicted operating temperature and / or a predicted rate of change of the operating temperature of the second traction engine.

[0032] The method can include predicting the operating temperature of at least the first and second traction motors as a function of an expected load on these motors. The load on the first and second traction motors is predicted based on one or more of the following: vehicle position data, driving speed, reference data on known geographical features, routes, speed limits, known or detected road conditions that may impose specific or special performance or load requirements, battery state of charge (SOC), external ambient air temperature or other climatic conditions, and estimated road load.

[0033] The method may include the proactive control of one or more vehicle cooling subsystems based on the predicted operating temperatures of the first and second traction motors. The method may include actuating one or more vehicle cooling subsystems to provide cooling based on the predicted operating temperatures of the first and second traction motors. The one or more vehicle cooling subsystems may consist of one or more of the following: a cooling fan, a coolant pump, and an active aerodynamic air deflector.

[0034] The method can include predicting vehicle stability for at least part of a current route. The method can include determining at least the first and second torque requirements based on the predicted vehicle stability.

[0035] According to a further aspect of the present invention, a method for controlling the operation of at least one first and one second traction motor in a vehicle is provided. The method can include predicting the vehicle stability for at least a portion of a current route. At least first and second torque requirements can be determined for the at least first and second traction motors. These torque requirements can be determined based on the predicted vehicle stability. The method can also include controlling the at least first and second traction motor control signals based on the determined torque requirements.

[0036] The method can include predicting vehicle stability depending on one or more of the following factors: a vehicle speed profile, a longitudinal acceleration profile, a lateral acceleration profile, and a coefficient of friction (µ).

[0037] According to another aspect of the present invention, a non-transitory, computer-readable medium is provided in which a series of instructions are stored which, when executed, cause a processor to perform the method described in this document.

[0038] Each control unit or controller described in this document may appropriately include a computing device with one or more electronic processors. The system may consist of a single control unit or electronic controller, or alternatively, different control functions may be embodied or housed in different control units or controllers. The terms "controller" or "control unit" as used in this document refer both to a single control unit or controller and to a plurality of control units or controllers operated together to provide a specified control functionality. To configure a controller or control unit, a suitable set of instructions may be provided which, when executed, cause the control unit or computing device to implement the control techniques described in this document.The set of instructions can be appropriately embedded in one or more electronic processors. Alternatively, the set of instructions can be provided as software, stored in one or more memory locations connected to the controller and executed on the computing device. The control unit or controller can be implemented as software running on one or more processors. One or more other control units or controllers can be implemented as software on one or more processors, optionally on the same one or more processors as the first controller. Other suitable arrangements can also be used.

[0039] Within the scope of this application, it is expressly intended that the various aspects, embodiments, examples, and alternatives presented in the preceding paragraphs, in the claims, and / or in the following description and drawings, and in particular their individual features, may be considered independently of one another or in any combination. This means that all embodiments and / or features of any embodiment may be combined in any way and / or in any combination, provided that these features are not incompatible.The applicant reserves the right to amend any originally filed patent claim or to file any new patent claim accordingly, including the right to amend any originally filed patent claim to depend on and / or incorporate any feature of any other claim, even if it has not previously been claimed in this manner. List of characters

[0040] One or more embodiments of the invention will now be described by way of example only with reference to the accompanying figures, wherein: Fig. 1 shows a schematic representation of a vehicle with a control system for controlling a torque distribution between a first and a second electric machine according to one aspect of the present invention, Fig. 2. A first block diagram shows the relationship between the control and the first and second in Fig. 1 illustrated electrical machine, Fig. Figure 3 shows a flowchart illustrating the operation of a prediction module according to the present invention, Fig. 4 shows a temperature profile curve of the first and second electric machines, which is predicted depending on route information for a current route of the vehicle, Fig. 5 shows a diagram that represents a deduction table for calculating the power loss deduction based on an operating temperature of the first electrical machine, Fig. Figure 6 shows the dynamic calculation of the temperature threshold and the target temperature as a function of the predicted operating temperature of the first and second electric machines for the current route, and Fig. Figure 7 shows a second block diagram illustrating the operation of the control system for predicting vehicle stability. DETAILED DESCRIPTION

[0041] A vehicle 1 with a control 2 One aspect of the present invention will now be described with reference to the accompanying figures. The vehicle 1 In the present embodiment, a battery-electric vehicle is used; however, the technical methods and devices described in this document can also be used in other vehicle types, for example, a hybrid electric vehicle (HEV) or a plug-in hybrid electric vehicle (PHEV). As in Fig. As shown in 1, the vehicle 1 in the present embodiment four wheels W1 - 4 , which are on the front and rear axles 3 , 4 are attached. The vehicle 1In the present embodiment, the vehicle has all-wheel drive; in operation, the torque is selectively applied to each of the wheels. W1 - 4 transferred to the vehicle 1 to propel the vehicle 1 It could be, for example, a passenger car, a commercial vehicle, or a sport utility vehicle.

[0042] The vehicle 1 consists of a first electric drive unit (EDU) 5 to transmit a first torque T1 on the front axle 3 and a second EDU 6 to transmit a second torque T2 on the rear axle 4 In the present embodiment, the first EDU 5 able to generate front torque TQ1 on the front wheels W1 , W2 of the vehicle 1 to transfer, and the second EDU 6 is capable of generating rear torque TQ2 on the rear wheelsW3 , W4 of the vehicle 1 to transfer. The term "front torque" used in this document refers to the torque at the front axle. 3 applied torque, the term "rear torque" used in this document refers to the torque applied to the rear axle 4 Applied torque. The total of the front and rear torques. TQ1 , TQ2 is at least substantially equal to a requested total torque TQ The front and rear torques TQ1 , TQ2 can be expressed as a percentage of the total requested torque TQ can be expressed. The front and rear torque. TQ1 , TQ2 are complementary and together correspond at least substantially to the required total torque TQ (i.e., 100%). The total requested torque can be generated depending on a driver's torque demand.

[0043] The first EDU 5 consists of a first electrical machine 7 , a first inverter 8 and a first gearbox / differential 9 The second EDU 6 consists of a second electric machine 10 , a second inverter 11 and a second gearbox / differential 12 The first and the second electric machine 7 , 10 Traction motors are used to generate torque for propelling the vehicle. 1 The first and the second electric machine 7 , 10 Each consists of a rotor and a stator (not shown). The first and second electric machines 7 , 10 These could be, for example, permanent magnet synchronous motors (PMSM). The first and second inverters 8 , 11are connected to a (not shown) traction battery to power the first and second electric machines 7 , 10 connected. The first and second inverters 8 , 11 They also perform the conversion of direct current to alternating current for AC motors. The control system 2 is for outputting the front and rear torque requirement signals DSF1 , DSF2 for controlling the operation of the first and second EDU 5 , 6 trained. As described in this document, the front and rear torque requirements indicate DSF1 , DSF2 the operation of the first and second electric machines 7 , 10 The control 2 This can involve the first and second torques. T1 , T2 on the front and rear axle 3 , 4 transmitted.

[0044] The control 2According to the present embodiment, the vehicle stability control (VSC) is... The control 2 consists of an electronic processor 13 , which is equipped with a storage device 14 is coupled. The storage device 14 consists of a set of non-transitory instructions which, when executed, direct the electronic processor 13 to initiate the execution of the procedure(s) described in this document. The control 2 will be connected to an interface 15 e.g. a communication bus, connected to communicate with the vehicles in the vehicle 1 to communicate with existing electronic control units (ECUs). The ECUs are usually identified by their reference number. 16 in Fig. 1 marked. The control 2 is designed to send an acceleration signal SA1 from an accelerator pedal sensor 17 receives, who is in the vehicle 1is assigned to the intended (not shown) accelerator pedal. The control 2 is also designed to send a braking signal SB1 from a brake pedal sensor 18 receives, who is in the vehicle 1 is assigned to the intended (not shown) brake pedal.

[0045] A schematic representation of the control system 2 is in Fig. 2 shown. The control 2 is designed to be a limit control module 20 , a driver demand assessment and arbitration module 21 , a traction and behavior control module 22 , a torque distribution module 23 and a torque shaping module 24 implements the limit value control module. 20 receives from the (not shown) controllers the first and second inverters 8 , 11assigned maximum and minimum limits. In some applications, the limit control module can 20 for each of the first and second electric machines 7 , 10 A pair of inverter limits is obtained to describe the peak power (i.e., motor / inverter power for a short period) and the continuous power (i.e., motor / inverter power for unlimited operation). The limit control module 20 It also receives a power limit from the traction battery and converts this into an equivalent torque limit for each of the first and second electric machines. 7 , 10 to, for example, divide the power limitation according to a current torque distribution between the first and second electric machine 7 , 10 The limit value control module 20 can be used for each of the first and second electric machines 7 ,10 Depending on one or more of these limit values, a maximum and a minimum limit value can be generated. The limit value control module 20 generates first and second limit control signals LCS1 , LCS2 The first limit control signal LCS1 represents the combined maximum and minimum limits of the powertrain. The second limit control signal LCS2 includes maximum and minimum limits for each of the first and second electrical machines 7 , 10 on the wheel frame, i.e., limits of operation, which are converted into a wheel reference frame taking into account the gear ratio and losses.

[0046] The first and second limit control signals LCS1 , LCS2 are connected to the driver demand assessment and arbitration module 21 or the traction and behavior control module 22 Issued. The driver demand assessment and arbitration module21 It receives driver input, including the acceleration signal. SA1 and the brake signal SB1 The driver demand assessment and arbitration module 21 It is used to generate a torque requirement signal. SDT1 depending on the acceleration signal SA1 and from the brake signal SB1 The torque requirement signal SDT1 consists of one on the front and rear axle 3 , 4 The total requested torque to be transmitted is either traction torque or energy recuperation torque. The requested total torque can be a positive (acceleration) torque (+ve) for transmitting drive torque to the wheels. W1 - 4 or a negative (braking) torque (-ve) to transfer a braking or energy recuperation torque to the wheels W1 -4. It goes without saying that the vehicle 1This can cause a delay if the positive (+ve) torque requirement is less than the total losses of the vehicle, e.g., when driving uphill. 1 can occur. Conversely, the vehicle can 1 accelerate when the negative (-ve) torque requirement is less than the total vehicle gain, e.g., when driving downhill. 1 This can occur. The requested total torque can be generated depending on a cruise control system or an adaptive speed control system. The present invention can be implemented in conjunction with one or more autonomous or semi-autonomous control module(s) that can generate at least the requested total torque. The torque demand signal SDT1 is connected to the traction and behavior control module 22 output. The torque distribution module 23is operational, in order to distribute the power to the front and rear axles 3 , 4 to control the transmitted torque so that the requested total torque is achieved.

[0047] The traction and behavior control module 22 is designed in such a way that torque is distributed between the front and rear axles 3 , 4 (i.e., a torque distribution between the front and rear axles) 3 , 4 ) is determined, which is necessary to maintain the dynamic stability of the vehicle 1 is suitable. The traction and behavior control module 22 is for determining the first and second torque ranges TR1 , TR2 formed, each responsible for the first and second area of ​​the front and rear axle respectively. 3 , 4 Define the torque to be transmitted. The first torque range TR1 can have a minimum value TQ1 (MIN) and a maximum value TQ1 (MAX) include; the second torque range TR2 can have a minimum value TQ2 (MIN) and a maximum value TQ21 (MAX) include. The first and second torque ranges TR1 , TR2 In the present embodiment, the percentage of the requested total torque is used. TQ expressed. In alternative embodiments, the first and second torque ranges can be TR1 , TR2 be expressed as torque values. The minimum value TQ1 (MIN) of the first torque range TR1 and the minimum value of the second torque range TQ2 (MIN) are both greater than or equal to zero (0) when the total requested torque TQ greater than or equal to zero (0). The maximum value TQ1 (MAX) of the first torque range TR1 and the maximum value of the second torque range TQ2 (MAX) are both less than or equal to zero (0) when the requested total torque TQ is less than or equal to zero (0). The front and rear torque TQ1 , TQ2 are complementary and, in combination, correspond at least substantially to the required total torque TQ (i.e., 100%). The first and second torque ranges TR1 , TR2 For example, they can be predefined depending on recorded operating conditions or driving styles. The traction and behavior control module 22 combines the first and second limit control signals LCS1 , LCS2 from the limit control module 20 with internally generated limits for stability and / or traction. Examples of traction and behavior control include: PEDAL POSITION

[0048] The traction and behavior control module 22 can the torque distribution between the front and rear axles3 , 4 Determine this depending on the accelerator pedal position and / or the brake pedal position. The traction and behavior control module 22 Depending on the accelerator pedal position and / or the brake pedal position, the scope of the first torque range can vary. TR1 and / or the second torque range TR2 determine. For example, the extent of the first and second torque ranges can vary. TR1 , TR2 inversely proportional to the magnitude of the braking torque demand generated by pressing the brake pedal. Alternatively or additionally, the traction and behavior control module can 22 the scope of the first and second torque ranges TR1 , TR2 Determine the range of the first and second torque ranges depending on the rate of change of the accelerator pedal position and / or the brake pedal position. TR1 , TR2 It can behave inversely proportional to a braking torque demand by depressing the brake pedal. Changes in the torque distribution and / or the extent of the first and second torque ranges. TRT1 , TR2 can be done in stages. Vehicle dynamics

[0049] The traction and behavior control module 22 can the torque distribution between the front and rear axles 3 , 4 depending on the longitudinal and / or lateral acceleration of the vehicle 1 determine. Alternatively or additionally, the traction and behavior control module can be used. 22 the torque distribution between the front and rear axles 3 , 4 Determine this depending on a vehicle speed profile and / or a coefficient of friction (µ). The traction and behavior control module 22depending on the longitudinal and / or lateral acceleration of the vehicle 1 the scope of the first and second torque ranges TR1 , TR2 determine. Alternatively or additionally, the traction and behavior control module can be used. 22 depending on the rate of change of the longitudinal acceleration and / or lateral acceleration of the vehicle 1 the scope of the first and second torque ranges TR1 , TR2 Determine the scope of the first and second torque ranges. TR1 , TR2 It can be inversely proportional to longitudinal and / or lateral acceleration. Changes to the torque distribution and / or the extent of the first and second torque ranges. TRT1 , TR2 These adjustments can be made in stages. At low longitudinal and lateral acceleration, the traction and behavior control module can be activated. 22For example, a torque distribution of 20 to 80% / 80 to 20% front / rear is possible. In this scenario, the first torque range TR1 a minimum value TQ1_TEMP (MIN) of 20% of the requested total torque TQ and a maximum value TQ1_TEMP (MAX) of 80% of the requested total torque TQ include, while the second torque range TR2 a minimum value TQ2_TEMP (MIN) of 20% of the requested total torque TQ and a maximum value TQ1_TEMP (MAX) of 80% of the requested total torque TQ This can include the traction and behavior control module. 22 This can restrict the distribution of front torque. At high longitudinal and lateral accelerations, the range of the first and second torque bands can be affected. TR1 , TR2 can be reduced, e.g., to 70 to 100% / 30 to 0% front / rear torque distribution. In this scenario, the first torque range TR1 a minimum value TQ1_TEMP (MIN) of 70% of the requested total torque TQ and a maximum value TQ1_TEMP (MAX) of 100% of the requested total torque TQ include, while the second torque range TR2 a minimum value TQ2_TEMP (MIN) of 0% of the requested total torque TQ and a maximum value TQ1_TEMP (MAX) of 30% of the requested total torque TQ may include. TQ1_TEMP TQ1_TEMP TQ2_TEMP TQ2_TEMP Any changes to the torque distribution and / or the scope of the first and second torque ranges TRT1 , TR2 These adjustments can be made in stages. It goes without saying that the first and second torque ranges... TR1 , TR2 are not equal to zero. In certain scenarios, the traction and behavior control module can 22 Specifying a discrete ratio for the front / rear torque distribution is, at least for certain aspects of the present invention, outside the scope of application. Estimated coefficient of friction (µ)

[0050] The traction and behavior control module 22 can determine the coefficient of friction (µ) of the surface under the wheels W1 - 4 of the vehicle 1 estimate. The traction and behavior control module 22 can the torque distribution between the front and rear axles 3 , 4 The traction and behavior control module controls the system based on the estimated coefficient of friction (µ). 22 can determine the scope of the first and second torque ranges TR1 , TR2 change depending on changes in longitudinal and / or lateral acceleration.

[0051] The first and second torque ranges TR1 , TR2 define minimum and maximum torque limits for the first and second EDU respectively. 5 , 6 . This defines the first torque range TR1 a minimum front torque and a maximum front torque for transmission to the front axle 3 , while the second torque range TR2 a minimum rear torque and a maximum rear torque for transmission to the rear axle 4 defined. The first torque range TR1 and / or the second torque range TR2 can provide a static, predefined torque range for the respective first and second electric machines 7 , 10, e.g., -3000 Nm to +3000 Nm in 10 Nm increments. Alternatively or additionally, the first torque range can include TR1 and / or the second torque range TR2 be limited by a minimum / maximum torque limit, e.g. depending on the operating speed of the respective first and second electric machines. 7 , 10 Alternatively or additionally, the first torque range TR1 and / or the second torque range TR2 can be determined depending on operating limits, e.g., one or more of the following groups: traction battery power limits, inverter limits, and transmission limits. Alternatively or additionally, the first torque range can be used. TR1 and / or the second torque range TR2 to be determined in order to maintain the dynamic stability of the vehicle. At least in certain embodiments, the first and second torque ranges can be TR1 , TR2 These areas may be dynamic and vary depending on current or predicted operating conditions.

[0052] The first and second torque ranges TR1 , TR2 are connected to the torque distribution module 23 output. The torque distribution module 23 It is used to control the power to the front and rear axles. 3 , 4 transmitted torque to achieve the requested total torque TQ to achieve. The torque distribution module 23 It serves to optimize the efficiency of the first and second electric machines 7 , 10 within the first and second torque ranges TR1 , TR2 In certain embodiments, the torque distribution module can 23 be designed in such a way that the combined overall efficiency of the first and second EDU 3 , 4is optimized, for example by taking into account the operating efficiencies of the first and second inverters 8 , 11 and / or the first and second gearbox / differential 9 , 12 As described in this document, the torque distribution module 23 designed to receive the front and rear torque demand signals DS1 , DS2 for controlling the operation of the first and second electric machines 7 , 10 generated. The front torque demand signal. DS1 includes a front torque requirement TQ1 for the first electric machine 7 and the rear torque requirement signal DS2 a rear torque requirement TQ2 for the second electric machine 10 The sum of each complementary pair of front and rear torque requirements TQ2s , TQ2 is at least substantially equal to the requested total torque TQ The torque distribution module 23 is for receiving the first and second engine speed signals MS1 , MS2 trained. The torque distribution module 23 is also for receiving the first and second temperature signals TS1 , TS2 the respective first and second EDU 5 , 6 trained. The first temperature signal TS1 consists of one or more of the following groups: a temperature of the first electrical machine 7 (Rotor and / or stator temperature), a temperature of the first inverter 8 and a temperature of the first gearbox / differential 9 The second temperature signal TS2 consists of one or more of the following: a temperature of the second electrical machine 10(Rotor and / or stator temperature), a temperature of the second inverter 11 and a temperature of the second gearbox / differential 12 The first temperature signal TS1 and / or the second temperature signal TS2 can be measured by one or more (not shown) sensors coupled to the respective components. Alternatively, the first temperature signal can be used. TS1 and / or the second temperature signal TS2 This can be estimated using appropriate thermal models, e.g., depending on operating conditions or loads of the respective components. The operation of the torque distribution module 23 to generate the front and rear torque requirement signals DS1 , DS2 .

[0053] The front and rear torque demand signals DS1 , DS2 are connected to the torque shaping module 24 output. The torque shaping module24 is designed to receive the front and rear torque demand signals DS1 , DS2 newly profiled and the front and rear final torque requirement signal DSF1 , DSF2 generated, which are connected to the respective first and second inverters 8 , 11 will be issued. The first and second inverters 8 , 11 control the operation of the first and second electric machines 7 , 10 depending on the front and rear final torque requirement signal DSF1 , DSF2 As described above, the first and second electric machines can 7 , 10 a positive torque for the propulsion of the vehicle 1 or a negative torque for decelerating the vehicle 1 generate. The first and second electric machines 7 , 10They can be designed to regenerate energy during braking, for example to recharge the traction battery.

[0054] The torque distribution module 23 is designed in such a way that it provides the appropriate torque distribution between the first and second drives 5 , 6 determined. The front and rear torque demand signals. DS1 , DS2 are generated in such a way that the front and rear torque requirements are met. TQ1 , TQ2 corresponding to the specified torque distribution. The torque distribution module 23 receives the first and second torque ranges TR1 , TR2 and determines the optimal torque distribution between the first and second EDU 5 , 6 , in order to achieve the requested total torque TQ to achieve the ratio between the requested total torque. TQ and the first and second torque ranges TR1 , TR2 is defined by the following equation: TQ = min ( TR1 ) + max ( TR2 ) = min ( TR2 ) + max ( TR1 )

[0055] The control 2 is trained to be a predictive module 25 for predicting the first and second operating temperatures PT1 , PT2 the first and second electric machine 7 , 10 as described in this document, the prediction module provides the first and second predicted operating temperatures. PT1 , PT2 for at least part of the vehicle's current route 1 ahead. The prediction module 25 It serves to assess whether the first and second predicted operating temperatures have been reached. PT1 , PT2 the respective first and second temperature thresholds TTH1 , TTH2 will be exceeded. The first and second temperature thresholds TTH1 , TTH2 can be predetermined, e.g., based on the operating parameters of the first and second electrical machines 7 , 10 The first and second temperature thresholds TTH1 , TTH2 They can, for example, correspond to a predetermined temperature above which the first and second electric machines 7 , 10 To prevent damage, the performance may be reduced. In the present embodiment, the first and second temperature thresholds are TTH1 , TTH2 for the first and second electric machine 7 , 10 the same. The evaluation can, for example, determine whether the first and second predicted operating temperatures are the same. PT1 , PT2 the respective first and second temperature thresholds TTH1 , TTH2 within a specified time period, e.g., within the next 5 or 10 minutes. Alternatively or additionally, the assessment can attempt to determine a specific time or time period at which the first and second predicted operating temperatures will be exceeded. PT1 , PT2 expected to be the respective first and second temperature thresholds TTH1 , TTH2 will be exceeded. The first temperature threshold TTH1 In the present embodiment, a maximum operating temperature is defined for the first electrical machine. 7 , above which the power of the first electric machine 7 must be downgraded. The second temperature threshold TTH2 In the present embodiment, a maximum operating temperature is defined for the second electrical machine. 10 , above which the power of the second electric machine 7must be downgraded.

[0056] The first and second predicted operating temperatures PT1 , PT2 are for a vehicle 1 The current route being traveled is determined. A route prediction algorithm can be used to predict the current route, e.g., depending on the vehicle's current position and destination. 1 The route prediction algorithm can be implemented using the prediction module. 25 It must be implemented.

[0057] Alternatively, the route prediction algorithm can be implemented by a separate module, e.g., a satellite navigation module. The current position of the vehicle. 1 can be achieved through one or more on-board navigation systems, such as a Global Positioning System (GPS), or through communication with an external device, such as a mobile phone connected to the vehicle. 1The destination is either fixed or determined by dead reckoning (DR) using a pre-defined position, with that position being updated for the current route based on known or estimated speeds over an elapsed time period. 1 The destination can be entered by the user, e.g., according to the destination specified in a satellite navigation system. Alternatively or additionally, the destination can be determined based on past destination data, e.g., by referencing one or more previous destinations.

[0058] The prediction module 25 uses to predict the respective first and second operating temperatures PT1 , PT2 The first and second thermal models are used to model the thermal behavior of the first and second electric machines. 7 , 10depending on the expected power consumption over the current route. In the present embodiment, the prediction module says 25 the first and second predicted operating temperatures PT1 , PT2 the first and second electric machine 7 , 10 depending on the expected power consumption along the current route. The first and second predicted operating temperatures. PT1 , PT2 will depend at least partially on the route information relating to the current route. INF1 determined. For example, the ones from the prediction module 25 The implemented first and second thermal models determine the load of each of the first and second electrical machines. 7 , 10 at least partially based on the route information INF1 predict the power consumption of the first and second electric motors for the current route. 7 , 10 This can vary depending on the load conditions along the current route, resulting in different first and second operating temperatures. PT1 , PT2 leads to the first and second electric machines. 7 , 10 They may need to generate different tractive and energy recovery torques, leading to uneven power consumption (and uneven heat distribution). These scenarios can prevail if there are significant elevation changes in the current route, e.g., when traveling uphill and / or downhill on a mountainous route. The first and second predicted operating temperatures PT1 , PT2 The load can be estimated for at least part of the current route depending on the predicted load. If the prediction module 25determined that the vehicle 1 If the same route has already been traveled partially or completely in the past, the prediction module can 25 If necessary, historical data for this particular route may be used. This historical data may include temperature data from one or more of the first and second electric machines. 7 , 10 The temperature was measured by the assigned temperature sensors. Alternatively or additionally, the historical data may also contain load data relating to the first and second electric machines. 7 , 10 represent applied loads.

[0059] Route information INF1 The route information may include one or more of the following: road gradient, road curvature, road elevation profile (e.g., with positive and / or negative elevation changes on the current route), speed limits or restrictions, traffic light position(s), roundabout position(s), and data on traffic volume (congestion), roadworks, and other road obstructions. Alternatively or additionally, the route information may include... INF1 Past data includes one or more of the following groups: acceleration and / or deceleration rate, driving speed, average speed for a specific route, and driving style (which may be attributed to a specific driver). Alternatively or additionally, route information may be included. INF1 This includes information provided by one or more sensors on the vehicle. 1Measurements can be taken, e.g., of moving objects, pedestrians, cyclists, and other vehicles. Alternatively or additionally, route information can be used. INF1 The route information includes known or predicted ambient air temperature or weather conditions (e.g., precipitation) for part or all of the current route. At least part of the route information must be included. INF1 The information may be retrieved from a database. The database may be stored on a storage device located in the vehicle or accessible remotely, for example, via a wireless communication network. Suitable resources for some or all route information. INF1 These are the eHorizon system from Continental AG and the Car2X system from Siemens AG. Alternatively or additionally, the route information can be... INF1 It contains data generated by one or more vehicle sensors. These sensors can consist of, for example, one or more of the following: a radar system, an optical or infrared camera, a lidar scanner, an inertial sensor, and an accelerometer. The route information INF1 can refer to the entire current route or a part of the current route.

[0060] How the prediction module works 25 will now be based on a Fig. 3 block diagrams shown 100 described. The route prediction algorithm identifies the current route (BLOCK 101The identified route can correspond to an entire trip or comprise a rolling horizon, representing, for example, the next x km of the current route (e.g., an 8 km rolling horizon updated every 1 km or every 2 km). The route can be identified as soon as the user enters the destination into the satellite navigation or uses the route prediction algorithm described in this document. The route information is then accessed. INF1 accessed the predicted current route (BLOCK 102 As described in this document, the route information can be INF1 The prediction module can be obtained from a (locally or remotely stored) database and / or one or more vehicle sensors. 25 It is used to predict the total tractive force required at the wheels. W1-4 of the vehicle 1 during the journey along the predicted current route (BLOCK 103The required tractive force can also be related to road / load estimates, if necessary (BLOCK). 104 Alternatively or additionally, the traction requirement can be determined by the driver of the vehicle. 1 (BLOCK 105 ) identify, in order to take driving style into account. A prediction of the total tractive force required at the wheels is made. W1 - 4 of the vehicle 1 created. The prediction module 25 calculated depending on the predicted total tractive effort requirement and the route information INF1 a curve (or profile) of the torque distribution between the first and second electric machine 7 , 10 (BLOCK 106 The prediction module 25 Can the torque distribution between the first and second EDU 5 , 6to optimize the energy consumption of the drive system, fulfilling one or more of the following requirements, if applicable: vehicle stability, traction, and drivability. The temperature profile curve is calculated for each of the first and second electric machines. 7 , 10 calculated depending on one or more of the following groups: the calculated curve of the torque distribution between the first and second EDU 5 , 6 , the environmental conditions, the system / component temperatures, other vehicle sensor information and the route information INF1 (BLOCK 107 The temperature curves of the first and second electric machines 7 , 10 are associated with the first or second temperature threshold TTH1 , TTH2 compared (BLOCK 108 If neither the first nor the second predicted operating temperature PT1 , PT2 the first and second temperature threshold TTH1 , TTH2 The algorithm terminates (END) if one or both of the first and second predicted operating temperatures are exceeded. PT1 , PT2 the respective first and second temperature thresholds TTH1 , TTH2 exceeding, the prediction module identifies 25 Possibilities for more effective cooling and / or increased torque distribution between the first and second electric machine 7 , 10 (BLOCK 109 The predicted temperature profiles can optionally be used to control one or more cooling subsystems in the vehicle. 1 and / or to optimize the control of the first and second electric machines 7 , 10 can be used. The prediction module 25It outputs control signals that include a predictive torque split requirement and / or a predictive cooling subsystem requirement. The predictive torque split requirement can be expressed as a target temperature curve and a closed-loop control that acts on the torque split to keep the simulation error within a predefined tolerance. The tolerance can, for example, be proportional to the expected operating temperature of the traction motors.

[0061] The control 2 receives the control signals from the prediction module 25 and performs a final arbitration between anticipatory and non-anticipatory torque sharing needs and / or similar requirements for the cooling subsystem (BLOCK 110 The non-predictive control systems in the control system 2 , such as the torque distribution module 23, receive current vehicle operating parameters and output a non-predictive torque distribution requirement and / or requirements to the cooling subsystem (BLOCK 111 The current vehicle operating parameters may include one or more of the following settings: vehicle speed (VREF), accelerator pedal position, brake pedal position, traction motor operating temperatures, and high-voltage (HV) battery power consumption. It is understood that the vehicle's current operating parameters may be measured and / or estimated. The control 2 Depending on the received predictive and non-predictive signals, it determines an appropriate compensation. The control system 2 gives the final torque requirement signals DSF1 , DSF2 according to the final torque distribution between the front and rear axles 3 , 4and / or the final control signals of the cooling subsystem.

[0062] If one or both of the first and second predicted operating temperatures PT1 , PT2 through the prediction module 25 the first and second temperature threshold TTH1 , TTH2 The prediction module can exceed 25 Possibilities for a more effective torque distribution between the first and second electric machine 7 , 10 characterize. In particular, the first and second electrical machines can 7 , 10 depending on the predicted temperature curves of the first and second electric machines 7 , 10 for part or all of the current route. The torque distribution curve between the first and second electric motors. 7 , 10will depend on the first and second predicted operating temperatures PT1 , PT2 certainly.

[0063] The torque distribution module 23 is designed in such a way that it determines the proportion of power from each of the first and second electrical machines 7 , 10 generated requested total torque TQ determined. According to one aspect of the present invention, the torque distribution between the first and the second electric machine is determined. 7 , 10 controlled in such a way that the time span during the current route is increased and preferably maximized when the operating temperature of the first and second electric machines 7 , 10 below the first and second temperature thresholds TTH1 , TTH2 lies. In the present embodiment, the first and second performance deductions are PP1 , PP2 with regard to the predicted operating temperatures PT1 , PT2 the first and second electric machine 7 , 10 calculated for the current route.

[0064] The first and second deductions PP1 , PP2 for each of the first and second electric machines 7 , 10 calculated. The first and second deductions PP1 , PP2 are applied to counteract a tendency against activating either the first or second electrical machine 7 , 10 to provide for when the prediction module 25 determines that the predicted operating temperatures PT1 , PT2 the first and second electric machine 7 , 10 the first or second temperature threshold TTH1 , TTH2 will be exceeded.

[0065] A first mechanical power factor results from the multiplication of the front torque requirement. TQ1 and the operating speed of the first electric machine 7 The first mechanical power factor and a first deduction factor W1 are multiplied together to calculate the first performance deduction PP1 to determine. The relationship between a first deduction factor W1 and an operating temperature of the first electric machine 7 is in a first in Fig. 5 deduction table shown 33 Illustrated. The first deduction table. 33 provides a deduction table for calculating the first deduction factor W1 depending on the first predicted operating temperature PT1 the first electric machine 7 as in Fig. The first deduction factor is shown in section 5. W1at a minimum (e.g. zero) when the first predicted operating temperature PT1 less than or equal to a first target temperature PT1target for the first electric machine 7 is. The first deduction factor W1 increases when the first predicted operating temperature is reached. PT1 is greater than the first target temperature PT1 target for the first electric machine 7 A second mechanical power factor results from the multiplication of the rear torque requirement. TQ2 and the operating speed of the second electric machine 10 A second deduction factor W2 is derived from a (not shown) second deduction table depending on the predicted operating temperature PT2 the second electric machine 10 derived. The second deduction factor W2 is at a minimum (e.g. zero) when the second predicted operating temperature PT2 below a second target temperature PT2target for the second electric machine 10 lies. The second deduction factor W2 increases when the second predicted operating temperature PT2 is greater than the second target temperature PT2 target for the second electric machine 10 The second mechanical power factor and the second deduction factor W2 are multiplied together to calculate the second performance deduction PP2 to determine. It is understood that the first and second deductions are PP1 , PP2 into the first and second motor cards for the first and second electric machine 7 , 10 can be integrated. For example, the first and second motor cards can include a buffer that corresponds to the temperature of the respective first and second electric motors. 7 , 10is connected to give the torque distribution a tendency away from one or the other of the first and second electric machines 7 , 10 to award when the operating temperature of the respective first and second temperature thresholds TTH1 , TTH2 approaching the first target temperature PT1 target and / or the second target temperature PT2target These can be fixed values. Alternatively, as described below, the first target temperature can be... PT1 target and / or the second target temperature PT2target They are calculated dynamically.

[0066] The first deduction of benefits PP1 will be increased when the first predicted operating temperature is reached. PT1 (i.e., the predicted operating temperature of the first electric machine) 7 ) the first temperature threshold TTH1 is expected to be exceeded within a predetermined time period or distance. Alternatively or additionally, the first deduction of benefits may be PP1 will be increased if the rate at which the first predicted operating temperature is reached PT1 increases, a first predetermined rate change threshold (corresponding to a slope of the first predicted operating temperature) PT1 ) within a predetermined time period or distance. The second deduction PP2 is increased when the second predicted operating temperature PT2 (i.e., the predicted operating temperature of the second electric machine) 10 ) the second temperature threshold TTH2 is expected to be exceeded within a predetermined time period or distance. Alternatively or additionally, the second deduction may be applied. PP2 will be increased if the rate at which the second predicted operating temperature PT2 increases, within a predetermined time period or distance a second predetermined threshold for the rate of change (corresponding to a slope of the second predicted operating temperature) PT2 ) exceeds.

[0067] The torque distribution module 23 is designed in such a way that it reduces the proportion of the power supplied by the first electrical machine 7 generated requested total torque depending on an increase in the first power deduction PP1 reduced. The torque distribution module 23 is designed in such a way that it reduces the proportion of the power supplied by the second electric machine 10 generated requested total torque depending on an increase in the second power deduction PP2 reduced. The torque distribution module 23It may be designed in such a way that the front and rear torques TQ1 , TQ2 within the first and second phases, respectively, through the traction and behavior control module 22 specific torque ranges TR1 , TR2 be determined.

[0068] The first deduction of benefits PP1 can be derived from the first deduction table 33 depending on the predicted operating temperature PT1 the first electric machine 7 be derived. The first deduction PP1 can be proportional to the level of the predicted operating temperature PT1 the first electric machine 7 behavior. Alternatively or additionally, the first deduction in benefits can PP1 proportional to the time period in which the predicted operating temperature PT1 the first electric machine 7 above the first temperature threshold TTH1 The prediction module is located. 25 could, for example, be the curve of the first predicted operating temperature PT1 to include in relation to the timing. The second deduction of benefits PP2 can be derived from a second assignment table depending on the predicted operating temperature PT2 the second electric machine 10 can be derived. The second deduction PP2 can be proportional to the level of the predicted operating temperature PT2 the second electric machine 10 behavior. Alternatively or additionally, the second deduction may apply. PP2 proportional to the time period in which the predicted operating temperature PT2 the second electric machine 10 above the second temperature threshold TTH2 The prediction module is located. 25For example, the curve of the second predicted operating temperature could be included in relation to the time period.

[0069] As described above, the first target temperature can be set PT1 target and / or the second target temperature PT2target are calculated dynamically. A second diagram 300 with the illustration of a dynamically calculated first temperature threshold TTH1 is in Fig. 6 shown. As in Fig. As illustrated in section 6, the first target temperature is shown. PT1 target calculated as a function of power degradation events when the output torque of the first electric machine 7 The power is limited, for example, to prevent damage from overheating. Power reduction events occur when the first predicted operating temperature is exceeded. PT1 the first temperature threshold TTH1 exceeds. This allows the prediction module 25Predict when one or more power degradation events will occur during the current route. The first target temperature. P1 target is based on the first predicted operating temperature PT1 Calculated at the end of successive power reduction events. The first target temperature PT1 The target consists of a target line that represents the first predicted operating temperature. PT1 at the end of an initial power degradation event with the first predicted temperature PT1 at the end of a second power reduction event. The target curve in the present embodiment is linear, but can also be non-linear, e.g., consist of a curve. As in Fig. As shown in Figure 6, the first and second power degradation events are successive power degradation events that depend on the first predicted temperature. PT1 The end of each power reduction event is characterized by the fact that the first predicted temperature PT1 below the first temperature threshold TTH1 falls. The first temperature target PT1 target can be used as a dynamic breakpoint. The first temperature threshold TTH1 It could also be viewed as a dynamic holding point that can be lowered to provide a control reserve for further power reduction events of the first electric machine. 7 to create along the current route. Regarding Fig. 5 can all intermediate stops x1 , xn between the first target temperature PT1 target and the first temperature threshold TTH1 as a percentage of the interval between the first target temperature PT1 target and the first temperature threshold TTH1 be expressed. It is understood that the second target temperature PT2target using the same technical method with regard to the second predicted temperature PT2 and the second temperature threshold TTH2 can be calculated.

[0070] The torque distribution module 23 generates a front torque demand signal DS1 with a front torque TQ1 and a rear torque requirement signal DS2 with a rear torque TQ2 The front and rear torque demand signals DS1 , DS2 are connected to the torque shaping module 24 output. The torque shaping module 24 gives the final front and rear torque requirement signals. DSF1 , DSF2 to the first or to the second inverter 8 , 11 out. The first and second electric machines 7 , 10 will depend on the final front and rear torque requirement signals. DSF1 , DSF2 controlled to distribute front and rear torque TQ1 , TQ2 on the front and rear axles 3 , 4 to transmit. The front and rear torques TQ1 , TQ2 are complementary and correspond at least substantially to the required total torque.

[0071] A first diagram 200 with an exemplary representation of the curve of the first and second predicted operating temperatures PT1 , PT2 for a current route is in Fig. 4 shown. In the example shown, the prediction module says 25 assuming that the first predicted operating temperature PT1 the first temperature threshold TTH1 at a first distance d1 will be exceeded and that the first predicted operating temperature PT1 until a second point in time t2 above the first temperature threshold TTH1 will remain. During the first interval ( d1 until d2 ) determines the prediction module 25 , that the second predicted operating temperature PT2 below the second temperature threshold TTH2 will remain. The prediction module 25 This first distance interval identifies ( d1 until d2 ) as a way to reduce the proportion of the power supplied by the second electric machine 10 to increase the generated requested total torque. By detecting this possibility early (i.e., before the distance) d1 ) can the prediction module 25 the proportion of the power from the second electric machine 10 Increase the generated requested total torque in advance, before the first predicted operating temperature PT1 the first temperature threshold TTH1 exceeds the operating temperature of the first electric machine, at least in certain scenarios.7 be reduced. The forecast module 25 Can the first and second predicted operating temperatures PT1 , PT2 Update either in real time or at predetermined intervals (time or distance). Further options for adjusting the torque distribution are available in relation to the intervals. d3 until d4 , d5 until d6 etc. in Fig. Figure 4 illustrates this. It is understood that different operating conditions apply to the vehicle. 1 This can lead to the second predicted operating temperature being exceeded. PT2 above the second temperature threshold TTH2 increases. At least in certain embodiments, the advance control of the first and second electric machines is possible. 7 , 10This offers efficiency advantages in managing their respective operating temperatures. The need to activate vehicle cooling subsystems, such as active cooling fins and cooling pumps, can be reduced. For example, if the temperature of the first electric motor exceeds 7 the first temperature threshold TTH1 , e.g. in the first interval d1 until d2 in which Fig. In scenario 4, the power output of the first electric machine would have to be 7 The system will be downgraded and the vehicle cooling subsystems will operate in high-performance mode to lower the operating temperature. The torque distribution between the first and second electric motors will be adjusted in advance. 7 , 10 before exceeding the first temperature threshold TTH1 through the first electric machine 7This can reduce the need to activate the vehicle's cooling subsystems. It is understood that predicting the operating temperature of the first and second electric motors is beneficial. 7 , 10 It can also enable the vehicle's cooling subsystems to be activated in advance, for example to allow operation in more efficient cooling modes.

[0072] The first and second temperature thresholds TTH1 , TTH2 These can be fixed values. However, in certain embodiments, the first and second temperature thresholds can be different. TTH1 , TTH2 can be calculated dynamically. In certain embodiments, the prediction module can 25 the first temperature threshold TTH1 and / or the second temperature threshold TTH2 depending on the first and second predicted temperatures PT1 , PT2 configure. Configure the prediction module 25For example, if it is determined that insufficient cooling capacity is available during part of the current journey, the first temperature threshold can be set. TTH1 and / or the second temperature threshold TTH2 before the predicted scenario. This will be reduced in Fig. 6 by a lowered first temperature threshold TTH1LOW illustrated. Conversely, the first temperature threshold can TTH1 and / or the second temperature threshold TTH2 will be increased before the predicted scenario if the prediction module 25 determines that excess cooling capacity is available during part of the current journey.

[0073] As described above, the prediction module 25 the torque distribution between the first and second EDU 5 , 6 optimize to meet one or more of the following requirements: vehicle stability, traction, and drivability. The prediction module 25It can predict vehicle stability for a route segment based on an estimated vehicle speed profile and a predicted longitudinal acceleration. Alternatively or additionally, the prediction module can 25 predict vehicle stability depending on one or more of the following factors: a predicted lateral acceleration, an estimated coefficient of friction (µ) of the surface over which the vehicle travels 1 driving, or other conditions that affect the traction available to a moving vehicle. The prediction module 25 The vehicle stability can be affected under various dynamic operating conditions of the vehicle. 1 Predict, e.g., when approaching a curve and / or during slight acceleration. The prediction module 25 can adjust wheel slip for each wheel W1 - 4Predict based on road topology and / or driving style. Vehicle speed profile, longitudinal acceleration, and lateral acceleration can be predicted depending on the road topography, e.g., from route information. INF1 can be derived. The predicted lateral acceleration can be proportional to the curvature of the road and a predicted speed.

[0074] As in Fig. 2 shown, determines the control 2 The (past and current) vehicle speed, road gradient, and curvature are used. From this information, together with a road load / mass estimate, the expected lateral and longitudinal acceleration of the vehicle can be calculated. 1These parameters can be calculated. For example, longitudinal acceleration can be calculated using Newton's second law. Alternatively or additionally, one or more vehicle speed profiles, longitudinal acceleration, and lateral acceleration can be predicted based on historical data, such as dynamic data previously recorded for the same route or a route with similar topographical features.

[0075] The coefficient of friction (µ) represents the friction between the vehicle wheels. W1 - 4 and a driving surface, e.g. a roadway, on which the vehicle 1A friction coefficient estimator (not shown) can improve the prediction. Alternatively, the friction coefficient (µ) can be estimated based on prevailing conditions, such as local weather conditions on the current route, and / or historical data recorded for the current route. The friction coefficient (µ) can be determined by communicating with other vehicles on the current route, either through direct communication between the vehicle and the vehicle. 1 and other vehicles (vehicle-to-vehicle communication) or through indirect communication with the other vehicles (vehicle-to-infrastructure communication). The coefficient of friction estimator can be local (i.e., by a sensor inside the vehicle). 1The friction coefficient estimator can be implemented either on the existing processor or on a remote processor (e.g., a "cloud" processor). It can receive traction information from the other vehicle(s) and estimate a friction coefficient for specific segments or sections of the road. It is understood that the estimated friction coefficient is time-dependent, as weather and road conditions are constantly changing.

[0076] Driver identification can be used to improve the technical prediction methods described in this document. The prediction module 25The system can predict the vehicle speed profile, longitudinal acceleration, and lateral acceleration depending on driving style, for example, by deriving these predictions from past dynamic data stored for a specific driver. Each driver has a variable threshold for lateral acceleration. Based on past information, the prediction module can 25 Modeling driver behavior to predict, for example, the relationship between lateral acceleration and road curvature. The prediction module 25 It can predict driver characteristics in relation to longitudinal acceleration, e.g., a speed profile when starting and / or exiting roundabouts, intersections, changes in the applicable legal maximum speed, etc.

[0077] The predicted vehicle stability can define the limits of the traction stability system. The limits of the traction stability system can include maximum and minimum limits for each of the first and second electric motors. 7 , 10 This includes the wheel frame, i.e., actuation limits that are converted into a wheel reference frame, taking into account the gear ratio and losses. The predicted vehicle stability can be used to determine the first and second torque ranges. TR1 , TR2 can be used. The torque distribution module 23 can the front and rear torques TQ1 , TQ2 within the resulting torque ranges TR1 , TR2 determine. At least in certain embodiments, this can improve the prediction of the drive system state and thus enable improved optimization to reduce thermal power reductions. For example, the initial power reduction can PP1 and / or the second deduction PP2 can be determined depending on the predicted vehicle stability.

[0078] How the prediction module works 25 To determine vehicle stability, a method is now used in Fig. 7 shown second block diagram 400 described. The route prediction algorithm identifies the current route (BLOCK 401The identified route can correspond to an entire trip or comprise a rolling horizon, representing, for example, the next x km of the current route (e.g., an 8 km rolling horizon updated every 1 km or every 2 km). The route can be identified as soon as the user enters the destination into the satellite navigation or uses the route prediction algorithm described in this document. The route information is then accessed. INF1 accessed the predicted current route (BLOCK 402 The route information INF1 The current position of the vehicle can be obtained from a (locally or remotely stored) database and / or one or more vehicle sensors. 1 can be determined from a navigation system that includes, for example, a GPS (Global Positioning System) module. The prediction module 25 It serves to predict the total tractive force required at the wheels. W1- 4 of the vehicle 1 during the journey along the predicted current route (BLOCK 403 The required tractive force may also refer to road / load estimates (BLOCK). 404 Alternatively or additionally, the traction requirement can be determined by the driver of the vehicle. 1 (BLOCK 405 ) identify, in order to take driving style into account. A prediction of the total tractive force required at the wheels is made. W1 - 4 of the vehicle 1 Created based on the predicted total tractive effort requirement and route information. INF1 says the prediction module 25 the limits of the traction stability system are preceded by the predicted maximum and minimum limits for each of the first and second electric machines 7 , 10 consist (BLOCK 406The operation of the drive and cooling systems is controlled depending on the predicted limit values ​​of the traction stability system (BLOCK). 407 ) to improve or optimize efficiency.

[0079] It should be noted that various modifications can be made to the embodiment(s) described in this document without deviating from the scope of the attached claims.

[0080] The embodiment described in this document relates to a vehicle 1 with one electric motor per axle. It is understood that aspects of the present invention may also be applicable to other vehicle types with differently configured electric drive trains. The present invention has been described with reference to an embodiment in which the first electric motor 7 with the front axle 3 and the second electric machine 10with the rear axle 4 are coupled. It is understood that the first and second electric machines are 7 , 10 can be designed in such a way that they transfer the torque to the same axis (either the front axle) 3 or the rear axle 4 ) or even on the same wheel W1 - 4 transferred. Furthermore, the present invention can be used in a vehicle 1 with more than two electric machines 7 , 10 can be applied. For example, the vehicle 1 consisting of three (3) or four (4) electrical machines that can be operated to generate a traction torque and / or a regeneration torque.

Claims

[1] Control (2) for controlling the operation of at least one first and one second traction machine (7, 10) in a vehicle (1), wherein the control (2) comprises a processor configured to: an operating temperature (PT1, PT2) of each of the at least first and second traction engines (7, 10) for at least part of a current route, at least the first and second torque requirements (DS1, DS2) for the at least first and second traction machine (7, 10) are determined, wherein the at least first and second torque requirements (DS1, DS2) are determined as a function of the predicted operating temperatures (PT1, PT2) of the at least first and second traction machine (7, 10), at least first and second drive motor control signals (DSF1, DSF2) are generated depending on the specified at least first and second torque request (DS1, DS2), and at least first and second power loss deductions (PP1, PP2) depending on the predicted operating temperatures (PTA, PT2) of the at least first and second traction machine (7, 10) determined, wherein the processor is configured to determine a first predicted time at which the operating temperature of the first traction machine (7) is expected to exceed a first temperature threshold (TTH1), and to apply the first power loss deduction (PP1) a predetermined first time interval before the first predicted time, wherein the duration of the first time interval is proportional to the predicted operating temperature (PT1) and / or a predicted rate of change of the operating temperature (PT1) of the first traction machine (7). [2] Control (2) according to claim 1, wherein the at least first and second power loss deduction (PP1, PP2) are proportional to the predicted operating temperature (PT1, PT2) or a predicted rate of change of the operating temperature (PT1, PT2) of the at least first and second traction machine (7, 10). [3] Control (2) according to claim 1 or claim 2, wherein the processor is configured to determine the at least first and second torque requirement (DS1, DS2) depending on the at least first and second power loss deductions (PP1, PP2). [4] Controller (2) according to one of claims 1, 2 or 3, wherein the processor is configured such that it: a second predicted time at which the operating temperature (PT2) of the second traction machine (10) is expected to exceed a second temperature threshold (TTH2), and the second power loss deduction (PP2) applies a predetermined second time period before the second predicted time, wherein the duration of the second time period is proportional to the predicted operating temperature (PT2) and / or a predicted rate of change of the operating temperature (PT2) of the second traction machine (10). [5] Control (2) according to one of the preceding claims, wherein the processor is configured to predict the operating temperature (PT1, PT2) of the at least first and second traction machine (7, 10) as a function of an expected load of each of the at least first and second traction machine (7, 10). [6] Control (2) according to one of the preceding claims, wherein the processor is configured to predict the vehicle stability for at least the part of the current route and to determine the at least first and second torque request (DS1, DS2) depending on the predicted vehicle stability, wherein the vehicle stability is predicted depending on one or more of the following factors: a vehicle speed profile, a longitudinal acceleration profile, a lateral acceleration profile and a coefficient of friction (µ). [7] Vehicle (1) with a control system (2) according to one of the preceding claims. [8] Method for controlling the operation of at least one first and one second traction machine (7, 10) in a vehicle (1), the method comprising: Predictions of an operating temperature (PT1, PT2) of each of the at least first and second traction motors (7, 10) for at least part of a current route, Determining at least first and second torque requirements (DS1, DS2) for the at least first and second traction machine (7, 10), wherein the at least first and second torque requirements (DS1, DS2) are determined as a function of the predicted operating temperatures (PT1, PT2) of the at least first and second traction machine (7, 10), Control of at least the first and second drive motor control signals (DSF1, DSF2) depending on the determined at least first and second torque request (DS1, DS2), Determining at least one first and one second power loss deduction (PP1, PP2) depending on the predicted operating temperatures (PTA, PT2) of the at least first and second traction machine (7, 10), and Determining a first predicted time at which the operating temperature of the first traction machine (7) is expected to exceed a first temperature threshold (TTH1), wherein the first power loss deduction (PP1) is applied a predetermined first time interval before the first predicted time, the duration of the first time interval being proportional to the predicted operating temperature (PT1) and / or a predicted rate of change of the operating temperature (PT1) of the first traction machine (7). [9] Method according to claim 8, wherein the at least first and second power loss deduction (PP1, PP2) is proportional to the predicted operating temperature (PT1, PT2) or a predicted rate of change of the operating temperature (PT1, PT2) of the at least first and second traction machine (7, 10). [10] Method according to claim 8 or claim 9, wherein the method comprises determining the at least first and second torque requirement (DS1, DS2) depending on the at least first and second power loss deduction (PP1, PP2). [11] Method according to one of claims 8, 9 or 10, wherein the method comprises determining a second predicted time at which the operating temperature (PT2) of the second traction machine (10) is expected to exceed a second temperature threshold (TTH2), and applying the second power loss deduction (PP1) for a predetermined second time period before the second predicted time period, wherein the duration of the second time period is proportional to the predicted operating temperature (PT2) and / or a predicted rate of change of the operating temperature (PT2) of the second traction machine (10). [12] Method according to any one of claims 8 to 11, wherein the method comprises predicting the operating temperature (PT1, PT2) of the at least first and second traction machine as a function of an expected load of each of the at least first and second traction machine. [13] Method according to any one of claims 8 to 12, wherein the method comprises predicting the vehicle stability for at least part of a current route and determining the at least first and second torque requirements (DS1, DS2) as a function of the predicted vehicle stability, wherein the method comprises predicting the vehicle stability as a function of one or more of the following factors: a vehicle speed profile, a longitudinal acceleration profile, a lateral acceleration profile and a coefficient of friction (µ). [14] Non-transitory computer-readable medium with a set of instructions stored therein which, when executed, cause a processor to execute the method claimed in any one of claims 8 to 13.

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