Microclimate system based on car seats

Abstract

A microclimate system for vehicle occupants includes a plurality of microclimate thermoeffectors. Each microclimate thermoeffector at least partially controls the climate in at least one of a plurality of occupant zones. Each microclimate thermoeffector includes a sensor configured to determine microclimate temperature data corresponding to the zone. A controller includes an input configured to receive vehicle temperature data from a vehicle data bus, the vehicle temperature data including cabin temperature and outside air temperature. The controller fuses the microclimate temperature data with vehicle temperature data and determines an estimated local equivalent temperature for each microclimate thermoeffector. The controller also provides a temperature command to each microclimate thermoeffector based on the estimated local equivalent temperature corresponding to the microclimate thermoeffector.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application No. 62 / 937,890, filed on November 20, 2019. Technical Field

[0003] The present disclosure relates to a microclimate system that utilizes sensor fusion and fuzzy logic to provide enhanced thermal comfort to occupants. Background Art

[0004] In traditional automotive HVAC or climate systems, the control system uses temperatures from sensors installed in various locations within the cabin or calculates the temperature using a mathematical cabin thermal model. In recent years, seat-based microclimate systems have become more desirable because they achieve comfort faster and use less energy than existing systems.

[0005] Car seat-based microclimate systems incorporate a variety of conductive, convective, and radiative devices, such as heating pads, thermoelectric devices (TEDs), positive temperature coefficient thermistors (PTCs), and small compressor systems located within the seat and surrounding area. Accurately calculating local temperatures to control heating / cooling devices is crucial for controlling local thermal comfort, but this approach is difficult to achieve in current systems.

[0006] Current approaches for automotive seat-based microclimate systems are based on discrete on / off or modulated power (PWM) control with fixed temperature set points (typically in three to five discrete levels). The occupant manually selects one of these predefined temperature set points to adjust for the changing conditions of the vehicle and the human body. Furthermore, because the levels are discrete, users are forced to "hunt" for an unavailable setting by changing levels.

[0007] Fuzzy logic has been disclosed as an option for overall air heating and cooling in aircraft cabins. Fuzzy logic is an algorithmic approach that uses "degrees of truth" rather than binary extremes of true (1) / false (0). Fuzzy logic includes extreme cases, but also includes multiple states between true and false, so that a comparison between two things may produce a value between true and false (e.g., the pilot is comfortable is 0.45 (45%) true). Since fuzzy logic is used to regulate the overall air temperature, the rate of change of the cabin temperature is used to create the fuzzy set rather than another metric. Regulation based on the rate of change of temperature prevents undesirable cabin temperature oscillations beyond the desired cabin temperature. Summary of the Invention

[0008] In one exemplary embodiment, a microclimate system for a vehicle occupant includes a plurality of microclimate thermal effectors, each microclimate thermal effector configured to at least partially control the climate in at least one occupant zone of a plurality of defined occupant zones, each microclimate thermal effector comprising: a sensor configured to determine microclimate temperature data corresponding to the at least one occupant zone; a controller in communication with the microclimate thermal effector, the controller having an input configured to receive vehicle temperature data from a vehicle data bus, the vehicle temperature data including at least a cabin temperature and an outside air temperature, the controller configured to fuse the microclimate temperature data with the vehicle temperature data and determine an estimated local equivalent temperature for each microclimate thermal effector based on the fused data, the controller further configured to provide a temperature command to each microclimate thermal effector based on the estimated local equivalent temperature corresponding to the microclimate thermal effector.

[0009] Another example of the above microclimate system also includes a thermal control system in the vehicle, the thermal control system having a first temperature sensor exposed to conditioned air from the thermal control system.

[0010] In another example of any of the foregoing microclimate systems, the thermal control system in the vehicle is a heating, ventilation, and cooling (HVAC) system and the first temperature sensor is configured to detect cabin temperature.

[0011] Another example of any of the above microclimate systems includes a second temperature sensor exposed to air outside the vehicle, the second temperature sensor configured to detect a temperature of the outside air.

[0012] In another example of any of the foregoing microclimate systems, the plurality of zones includes at least two of a head zone, a seat back zone, a seat cushion zone, a hand / arm zone, and a foot / leg zone.

[0013] In another example of any of the above microclimate systems, the microclimate thermoeffector is selected from the group consisting of: a climate controlled seat, a headrest / neck adjuster, a climate controlled headliner, a steering wheel, a heated shifter, a heating mat, and a small compressor system.

[0014] In another example of any of the above microclimate systems, the controller is configured to apply a stratification bias to the cabin temperature to adjust for a location of the cabin temperature sensor.

[0015] In another example of any of the above microclimate systems, weighting factors are applied to the outside air temperature and the cabin temperature.

[0016] In another example of any of the above microclimate systems, a value of each weighting factor depends on at least one of season and climate zone.

[0017] In another example of any of the above microclimate systems, the vehicle temperature data includes vehicle solar load.

[0018] In another example of any of the above microclimate systems, the vehicle solar load is normalized and a weighting factor is applied to the vehicle solar load, wherein the weighting factor compensates for vehicle-specific characteristics.

[0019] In another example of any of the above microclimate systems, the vehicle temperature data includes vehicle speed.

[0020] In another example of any of the above microclimate systems, a weighting factor is applied to vehicle speed, wherein the weighting factor compensates for effectors in an area surrounding seats, including heating devices in door panels and a floor area.

[0021] In another example of any of the microclimate systems above, temperature feedback from at least one microclimate thermal effector is provided to the controller, and wherein the expected local temperature is determined for the at least one microclimate thermal effector based on the temperature feedback.

[0022] In another example of any of the above microclimate systems, the controller is configured to fuse the microclimate temperature data with the vehicle temperature data based on the following equation:

[0023] T local =W1×(T cabin +b tv )+W2×T outside +W3×SL nor +W4×V+W5×T lf

[0024] Where: W i i=1,2,3,4,5;calibrated weight factor

[0025] T cabin Cabin temperature

[0026] b tv Temperature vertical stratification factor or bias

[0027] T outside External temperature

[0028] SL nor Normalized solar load

[0029] V Vehicle speed

[0030] T lf Local effector temperature feedback

[0031] In another example of any of the microclimate systems above, the controller determines a unique estimated local equivalent temperature for each selected microclimate thermal effector based on the equation. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present disclosure may be further understood by reference to the accompanying drawings, which include Figure 1-9 .

[0033] Figure 1 Schematic illustration of a vehicle heating, ventilation and cooling system.

[0034] Figure 2 A sensor fusion processor for fusing microclimate sensor data and other vehicle sensor data into a single vehicle sensor set is schematically illustrated.

[0035] Figure 3 An exemplary thermal comfort ASHRAE scale ranging from -3 to 3 is schematically illustrated.

[0036] Figure 4A The figure shows the equivalent temperatures for various body regions during summer.

[0037] Figure 4B Figure 2 shows the equivalent temperatures for various body parts during winter.

[0038] Figure 5 The basic architecture of an exemplary microclimate control system is schematically illustrated.

[0039] Figure 6 An exemplary fuzzy logic control is schematically illustrated.

[0040] Figure 7A An exemplary temperature environment fuzzy set is schematically illustrated.

[0041] Figure 7B An exemplary temperature environment fuzzy set is schematically illustrated.

[0042] Figure 8 An example ΔT-based fuzzy set for a given thermal comfort effector is schematically illustrated.

[0043] Figure 9 An exemplary fuzzy logic controller output graph for heating is shown.

[0044] The embodiments, examples and alternatives of the claims or the following description and drawings, including any of their individual aspects or corresponding individual features, may be taken independently or in any combination. Features described in conjunction with one embodiment apply to all embodiments, unless these features are incompatible. DETAILED DESCRIPTION

[0045] The present disclosure relates to a microclimate system that provides enhanced thermal comfort to occupants by controlling microclimate thermal effectors using sensor fusion and fuzzy logic.

[0046] refer to Figure 1 Vehicle 100 has a heating, ventilation, and air conditioning (HVAC) system 110 for conditioning air 112 and controlling the overall temperature of the air within the vehicle cabin 102. A typical HVAC system 110 has ducting that supplies conditioned air 112 to the cabin 102 using a blower 114 that moves the air through a heat exchanger 116. Sensors 118 monitor the temperature of the conditioned cabin air 112, and a controller 120 regulates the operation of the HVAC system 110 to a temperature set point, which is typically manually adjusted by the occupant 104. In many scenarios, such as when multiple different occupants 104 are in the same cabin 102, a central HVAC 110 system is insufficient to achieve thermal comfort for each specific occupant 104 and each location. Therefore, microclimate devices or thermoeffectors are used to create a unique microclimate for each occupant 104 in the cabin 102, thereby providing enhanced overall thermal comfort for each occupant 104.

[0047] As an additional challenge to providing an efficient climate control system, each occupant 104 generally has unique personal comfort preferences. That is, a particular occupant 104 may perceive thermal energy levels differently than another occupant 104. Consequently, the exact same thermal environment within the vehicle 100 may be perceived as comfortable by one occupant 104 but uncomfortable by another occupant 104. To this end, the vehicle 100 includes a comprehensive approach to human thermal management that coordinates and optimizes the comfort of each occupant 104 of the vehicle 100 by utilizing fuzzy logic to control both the central HVAC system 110 or any other thermal control system in the vehicle 110, as well as various microclimate thermal effectors.

[0048] Continue to refer Figure 1 An example microclimate system may have multiple discrete occupant microclimate zones. According to ISO 145045-2:2006(E), the human body may be divided into different body segments such as hands, head, or chest, and each segment may have a different thermal comfort temperature range. Figure 1 The five example microclimate zones in FIG are: head 132, back 134, seat 136 (thighs and buttocks), feet / legs 138, and arms / hands 130. Fewer, more, and / or different zones may be used if desired, depending on the specific microclimate system and the requirements of a given vehicle. In the disclosed microclimate system, the local equivalent temperature T is estimated. localIt is calculated on a per-device / body-part basis, ie, for each individual region 130 , 132 , 134 , 135 , 136 , 138 .

[0049] Microclimate thermoeffector is the localized component that can adjust or maintain the desired microclimate in corresponding area 130,132,134,136,138.Microclimate thermoeffector can comprise such as climate control type seat (for example, U.S. Patent number 5,524,439 and 6,857,697), headrest / neck adjuster (for example, U.S. Provisional Application No. 62 / 039,125), climate control type roof lining (for example, U.S. Provisional Application No. 61 / 900334), steering wheel (for example, U.S. Patent number 6,727,467 and U.S. Publication No. 2014 / 0090513), heated shifter (for example, U.S. Publication No. 2013 / 0061603 etc.), heating pad, small compressor system and / or any other system that is configured to realize personalized microclimate.Enumerated microclimate thermoeffector is exemplary in nature and is non-restrictive. The microclimate system provides personal comfort to the corresponding occupant 104 in an automated manner with little or no input from the corresponding occupant 104. All or some of the microclimate thermoeffectors can be arranged to optimally control the thermal environment around the occupant of a seat located anywhere in a passenger vehicle. In addition, the microclimate thermoeffectors can be used to individually adjust the thermal comfort of individual segments of the occupant's body.

[0050] Occupant variables such as activity level and clothing are also considered by the local equivalent homogeneous temperature (EHT) model due to considerations of season, outside air temperature (determined via outside air sensor 118), and / or region. User information such as gender, height, weight, and age may also be provided to the sensor fusion processor in controller 120. By combining data from the vehicle data bus 140 (e.g., CAN, LIN, PWM HVAC signal, or any other data bus) with feedback from local conductive, radiative, or convective heating / cooling microclimate thermoeffectors within the headrest 150, seat back 152, seat cushion 154, floor mat 156, and steering wheel 158, each microclimate system accurately estimates a local equivalent homogeneous temperature or estimated local equivalent temperature T for the corresponding zone 130, 132, 134, 136, 138. local The local equivalent homogenized temperature or estimated local equivalent temperature is then used for local thermal comfort prediction and heating / cooling control. Thus, discrete local temperatures can be obtained at each of the five locations of the occupant's body using microclimate thermal effectors.

[0051] The sensor fusion method provides an efficient and accurate way to estimate the local ambient temperature at each microclimate zone 130, 132, 134, 136, 138. Figure 2 The sensor fusion processor 200 acquires cabin temperature / speed 202, outside air temperature 204, solar load 206, vehicle speed and / or data from the vehicle data bus 210 or from the vehicle sensors 160 (see Figure 1 ) and the sensor fusion processor includes a sensor fusion controller 210.

[0052] The sensor fusion controller 210 obtains temperature feedback from each thermoeffector (ie, each local heating / cooling device).An exemplary automotive seat-based occupant thermal comfort control system may utilize a number of conductive, convective, or radiant heating and cooling devices to achieve optimal occupant comfort.

[0053] In an example microclimate system, a plurality of microclimate thermoeffectors are configured to thermally regulate a plurality of passenger zones 130, 132, 134, 136, 138. Each of the microclimate thermoeffectors generates microclimate temperature data, which is provided by a temperature sensor (e.g., a negative temperature coefficient (NTC) element) incorporated into each microclimate thermoeffector 220. Non-limiting examples of microclimate thermoeffectors 220 include climate-controlled seats, headrest / neck adjusters, climate-controlled roof linings, steering wheels, heated shifters, heating pads, other heated surfaces, and small compressor systems. Other example microclimate thermoeffectors include radiant consoles and / or door surfaces, radiant heating panels, and liquid circuit-based cooling devices (devices that convert regulated glycol into localized cooling).

[0054] One or more controllers 230 within the sensor fusion controller 200 communicate with each microclimate thermal effector 220. The controller 230 includes one or more inputs 212 configured to receive vehicle temperature data from the vehicle data bus 210. The controller 230 fuses the microclimate temperature data 222 received from the microclimate thermal effector 220 with the vehicle temperature data received from the vehicle data bus 210 using an algorithm (e.g., Equation 1) to determine an estimated local equivalent temperature T for each microclimate thermal zone / area. local The controller estimates the local equivalent temperature T based on local To provide temperature commands 224 to each microclimate thermal effector 220 to achieve occupant thermal comfort at each individual zone 130 , 132 , 134 , 136 , 138 .

[0055] An example sensor fusion equation (Equation 1) calculates the estimated local equivalent temperature T for each microclimate thermal zone / region as follows local .

[0056] T local =W1×(T cabin+b tv )+W2×T outside +W3×SL nor +W4×V+W5×T lf

[0057] Where: W i i=1,2,3,4,5;calibrated weight factor

[0058] T cabin Cabin temperature

[0059] b tv Temperature vertical stratification factor or bias

[0060] T outside External temperature

[0061] SL nor Normalized solar load

[0062] V Vehicle speed

[0063] T lf Local effector temperature feedback

[0064] Vehicle temperature data includes cabin temperature T cabin , outside air temperature T outside , vehicle sunlight load SL nor and vehicle speed V. Weight factor W i The weighting factors may vary based on the specific microclimate thermal effector 220. One skilled in the art may select the specific weighting factors to be used for each control portion (i) based on the specific microclimate thermal effector 220 and the expected / experienced conditions of the thermal effector 220 that affects the control portion (i).

[0065] Most vehicles have a single interior air temperature sensor, but if one were to measure the local temperature within the vehicle at any given time, the temperature would be very different, especially if it is sunny that day (i.e. the vehicle has a high solar load). The algorithm allows for adjustments based on how closely the interior cabin sensor actually correlates to the local temperature and is unique to each vehicle. Vertical stratification or offset of temperature b tvThe cabin air temperature is adjusted at a tiered level for specific zones, such as the "breathing level" used in the area around the head of occupant 104. Similarly, if the cabin air temperature sensor is located at approximately the same level as the steering wheel, there may be no offset for back zone 134 and hand / arm zone 130. However, there may be a negative offset for foot / leg zone 138 or seat zone 136, and a positive offset for head zone 132. Weighting factor W1 provides further adjustment for each microclimate thermal zone / area 130, 132, 134, 136, 138. For example, the cabin temperature in head zone 132 may have a greater weighting factor W1 than that in hand / arm zone 130.

[0066] The weighting factor W2 adjusts the outside temperature and its effect on each microclimate thermal effector. For example, the outside temperature in the hand / arm zone 130 may have a greater weighting factor than the outside temperature in the seat zone 136. In cold environments, when the vehicle is traveling quickly, additional "work" from the door heaters is required to overcome heat loss through the doors and side glass.

[0067] Vehicle sunlight load SL nor is normalized, and a weighting factor W3 is applied to the vehicle sunlight load SL nor This can take into account specific vehicle body sections that are exposed to direct sunlight. For example, with a panoramic sunroof, more solar radiation heats the cabin and affects comfort. Conversely, if the vehicle has special sunshade glazing that reflects the solar load, this effect can be reduced.

[0068] Weighting factor W4 adjusts for the effect of vehicle speed on specific regions. The foot / leg region 138 is particularly susceptible to the effect of vehicle speed on local temperature. For example, in low-temperature, high-speed conditions, the foot / leg region 138 becomes particularly cold, so a larger weighting factor can be used for the foot / leg region 138. The effect of vehicle speed on, for example, the back region 134 is negligible, so a weighting factor can be used to cancel vehicle speed for the seatback thermoeffector.

[0069] Microclimate temperature data 222 includes thermal effector feedback T lf The thermoeffector feedback may also be adjusted using a weighting factor W5. For example, when a steering wheel heater is used, the thermoeffector 220 in the hand / arm region 130 may be given increased weighting because it may have a greater impact on occupant comfort in the hand / arm region 130.

[0070] The effectiveness of the disclosed system is further enhanced in some examples by using fuzzy logic to predict a person's thermal sensations, and thus their comfort, in real time. By employing fuzzy logic control, each device in the system automatically adjusts to the correct temperature and flow rate setpoints based on local environmental conditions to meet the desired thermal comfort levels for the occupant's local body segment. Because each occupant's thermal expectations are unique, fuzzy logic is used to define the temperature setpoint for each thermal effector in a manner that accounts for variations in thermal comfort across the occupant population.

[0071] In one example, the occupant thermal condition is expressed as the occupant's perception of hot or cold temperature or temperature changes and fluctuations. Figure 3 These hot and cold sensations are characterized by the ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) thermal sensation scale 310, shown in FIG. In the disclosed system, the PMV calculation assigns a "hot" / "cold" value to each microclimate zone.

[0072] As Figure 3 As an alternative to the thermal sensation scale shown in , the Berkeley Sensation and Comfort Scale (“Berkeley Scale”) described in, for example, the following document can be used to express occupant thermal conditions: Arens EA, Zhang H. & Huizenga C. (2006) Partial- and whole-body thermal sensation and comfort, Part I: Uniform environmental conditions. Journal of Thermal Biology, 31, 53-59. It should be understood that other methods can also be used to quantify the thermal condition of the occupant.

[0073] Season can significantly affect the perceived occupant thermal comfort, causing the PMV 320 results to be different. Therefore, the predicted occupant thermal comfort 400 can be adjusted based on the season, such as in Figure 4A and Figure 4B As shown in Figure 4A The graph shows equivalent temperatures for a plurality of (body) parts 410A during summer, and Figure 4B The figure shows the equivalent temperatures for a number of (body) parts 410B during winter. Figure 4A and Figure 4B Only a five-value thermal scale is shown ("too cold", "cold but comfortable", "neutral", "hot but comfortable" and "too hot"), but it is understood that thermal comfort can also be further refined to match Figure 3 The seven-value ASHRAE Thermal Sensation Scale 310 (3 to -3) shown in FIG.

[0074] Figure 5 The schematic diagram shows the basic architecture of an exemplary microclimate control system 500 that uses sensor fusion 510 and fuzzy logic control 520 (in Figure 6 The sensor fusion control scheme 500 compensates for important factors affecting occupant comfort, including both the ambient conditions 512 outside the vehicle and the ambient conditions 514 within a specific stratified layer of the cabin volume. In one example, the local effector temperature feedback T LF 532 (Feedback T) is provided by a negative thermal coefficient (NTC) temperature sensor integrated into each thermoeffector within each zone. The values ​​from the local fuzzy logic controller 520 and the NTC feedback 532 are provided to the PWM controller 540 to regulate the thermoeffector 530. Other control functions such as overheat protection, maximum temperature limit from the PWM controller, maximum hold time for a given temperature set point, etc. according to conventional control methods may also be used.

[0075] refer to Figure 5-6 The local fuzzy logic controller 520 establishes temperature-based fuzzy sets associated with the comfort temperature range for each local body segment. Fuzzy rules are created based on the characteristics and location of each physical heating / cooling device, and the fuzzy controller applies "fuzzy logic" to dynamically control the temperature of each individual heating / cooling device in the vehicle seat-based occupant thermal comfort system (including other microclimate thermal effectors).

[0076] As described above in conjunction with the sensor fusion algorithm, the occupant thermal comfort system is divided into multiple comfort control zones (e.g., five) based on up to nineteen body segments and corresponding effectors in each seat position. Depending on the unique circumstances surrounding the body, the number of control zones may be greater than five and may be as many as nineteen (as defined in the ASHRAE model). In some examples, from the perspective of user input to the system for customization and control, approximately five zones may be desirable due to reduced complexity, while a mathematical relationship between the five comfort control zones and, for example, nineteen zones may be established to translate comfort-related parameters into control-related parameters.

[0077] There may be several heating and / or cooling devices in each comfort control zone that have a significant effect on the climate. Each of these devices may have its own control module. Figure 5 The major functional subsystems within a typical heating and / or cooling control module 500 are shown.

[0078] After collecting vehicle data and feedback from all comfort control devices, the system generates local temperature information for each control module based on the device location. The control module calculates ΔT 550 based on the local temperature and the desired comfort temperature for the area. Specifically, ΔT 550 corresponds to the local temperature based on the vehicle temperature data minus the desired pre-set local comfort temperature for the given thermal effector. The fuzzy logic controller 520 takes ΔT 550 as input and converts ΔT 550 into a fuzzy membership function through fuzzification. Based on the ASHRAE thermal sensation scale, ISO 14505-2:2006 and the physical characteristics, location and corresponding body segment of each individual heating / cooling device, the exemplary system 500 defines the following: Figure 7A The four ambient temperature fuzzy sets 560, 562, 564, 566 (membership functions) for each zone are shown in FIG. Figure 7B The four fuzzy sets 570, 572, 574, and 576 for the heating / cooling set temperature are shown in FIG. The fuzzy logic controller 520 applies fuzzy rules and determines output values, i.e., the inference mechanism. Through defuzzification, the control module 540 converts the fuzzy outputs into real-life data values, which are used as the temperature set points for the device. Figure 6 This is a typical control flow chart used to design fuzzy logic controlled heating / cooling devices.

[0079] The temperature set point 552 is provided to the controller 540, which uses any suitable control scheme to provide a pulse width modulated (PWM) signal 542 to a given thermoeffector 530, controlling the thermoeffector 530 to reach the set point. The NTC within the thermoeffector 530 provides feedback to the sensor fusion algorithm 510 and the summing junction 534 between the temperature set point to provide a corrective signal to the control scheme.

[0080] The fuzzy sets account for the uncertainty associated with the application of the ASHRAE Thermal Perception Scale to any given occupant. A value of "1" indicates 100% certainty that the entire population would agree with the indicated thermal sensation, and a value of "0" indicates that the entire population would disagree with the indicated thermal sensation. Figure 7A and Figure 8 An example of a fuzzy set based on ΔT 550 for a given thermal comfort effector 530 is shown on the left side of FIG. The slope reflects the variation within the group as to whether the indicated thermal sensation is appropriate for the group of occupants. When the slopes overlap at a given ΔT 550, the group is divided as to its perceived thermal comfort. For example, at -10 ΔT 550, 50% of the group would feel "slightly cool" and 50% would feel "neutral." The fuzzy set is determined using ΔT 550 to generate a temperature set point 552 for a given thermal effector, as shown in FIG. Figure 7B and Figure 8As shown on the right side of Figure 7A 、 Figure 7B and Figure 8 The specific values ​​in are exemplary only, and these values ​​will vary depending on the specifics of the system 500 and the thermal effector 530 .

[0081] Figure 9 An exemplary fuzzy logic controller output graph 600 for heating is shown. Output graph 600 discloses a plurality of exemplary regions 610, 620, 630, 640, 650, where 610 represents a value of "0" where no user would be comfortable and 650 represents a value of "1" where every user would be comfortable. Intermediate regions 620, 630, 640 represent intermediate regions where some users are expected to be comfortable and others are expected to be uncomfortable.

[0082] Fuzzy logic temperature control can be based on SISO (single input single output) ID control or MIMO (multiple input multiple output) multi-dimensional control. Additional inputs and outputs can also be included, such as fan airflow rate, humidity, etc., and the control can be implemented according to any SISO or MIMO control scheme.

[0083] It should also be understood that although a particular component arrangement is disclosed in the illustrated embodiments, other arrangements will benefit therefrom. Although a particular order of steps is shown, described, and claimed, it should be understood that these steps can be implemented in any order, separately, or in combination, unless otherwise indicated, and will still benefit from the present invention.

[0084] Although different examples have specific components shown in the drawings, embodiments of the present invention are not limited to these specific combinations. It is possible to use some components or features from one example in combination with features or components from another example.

[0085] Although example embodiments have been disclosed, a worker of ordinary skill in this art would recognize that certain modifications would come within the scope of the claims. For that reason, the following claims should be studied to determine their true scope and content.

Claims

1. A microclimate system for vehicle occupants, comprising: a plurality of microclimate thermoeffectors, each microclimate thermoeffector configured to at least partially control the climate in at least one occupant zone of a plurality of defined occupant zones of an occupant of the vehicle, each microclimate thermoeffector including a sensor configured to determine microclimate temperature data corresponding to the at least one occupant zone; A controller in communication with the microclimate thermal effectors, the controller having an input configured to receive vehicle temperature data from a vehicle data bus, the vehicle temperature data including at least a cabin temperature and an outside air temperature, the controller configured to fuse the microclimate temperature data with the vehicle temperature data in a manner that accounts for vertical stratification of the cabin and determine an estimated local equivalent temperature for each microclimate thermal effector based on the fused data, the controller further configured to provide a temperature command to each microclimate thermal effector based on the estimated local equivalent temperature corresponding to the microclimate thermal effector. 2 . The microclimate system of claim 1 , further comprising a thermal control system in the vehicle, the thermal control system having a first temperature sensor exposed to conditioned air from the thermal control system.

3. The microclimate system according to claim 2, wherein: The thermal control system in the vehicle is a heating, ventilation, and cooling (HVAC) system, and the first temperature sensor is configured to detect a cabin temperature. 4 . The microclimate system of claim 2 , comprising a second temperature sensor exposed to air outside the vehicle, the second temperature sensor being configured to detect the outside air temperature.

5. The microclimate system according to claim 4, wherein: The plurality of regions include at least two of a head region, a seat back region, a seat cushion region, a hand / arm region, and a foot / leg region.

6. The microclimate system according to claim 5, wherein: The microclimate thermoeffector is selected from the group consisting of: a climate controlled seat, a headrest / neck adjuster, a climate controlled headliner, a steering wheel, a heated shifter, a heating mat, and a small compressor system.

7. The microclimate system according to claim 6, wherein: The controller is configured to apply a stratification bias to the cabin temperature to adjust for a location of a cabin temperature sensor.

8. The microclimate system according to claim 6, wherein: A weighting factor is applied to the outside air temperature and the cabin temperature.

9. The microclimate system according to claim 8, wherein: The value of each weighting factor depends on at least one of season and climate zone.

10. The microclimate system according to claim 6, wherein: The vehicle temperature data includes vehicle solar load.

11. The microclimate system according to claim 10, wherein: The vehicle solar load is normalized, and a weighting factor is applied to the vehicle solar load, wherein the weighting factor compensates for vehicle characteristics related to solar radiation effects.

12. The microclimate system according to claim 6, wherein: The vehicle temperature data includes vehicle speed.

13. The microclimate system according to claim 12, wherein: A weighting factor is applied to the vehicle speed, wherein the weighting factor compensates for effectors in the area surrounding the seats, including heating devices in the door panels and floor area.

14. The microclimate system according to claim 6, wherein: Temperature feedback from at least one microclimate thermal effector is provided to the controller, and wherein an expected local temperature is determined for the at least one microclimate thermal effector based on the temperature feedback.

15. The microclimate system according to claim 14, wherein: The controller is configured to fuse the microclimate temperature data with the vehicle temperature data based on the following equation: T local =W1×(T cabin +b tv )+W2×T outside +W3×SL nor +W4×V+W5×T lf Where: W i i=1,2,3,4,5; calibrable weighting factor T cabin Cabin temperature b tv Temperature vertical stratification factor or bias T outside External temperature SL nor Normalized solar load VVehicle speed T lf Local effector temperature feedback.

16. The microclimate system of claim 15, wherein: The controller determines a unique estimated local equivalent temperature for each selected microclimate thermal effector based on the equation.

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