Target cabin temperature determination for HVAC system of battery electric vehicle

Abstract

A control system for a battery electric vehicle comprises one or more processors. The processor(s) are configured to receive input data 302 indicative of one or more user body-related parameters (e.g. a metabolic and / or clothing parameter) and one or more environmental parameters (e.g. ambient temperature, relative humidity within a cabin of the vehicle and / or solar radiation). The processor(s) are also configured to receive an operating mode signal 304 indicative of a current operating mode of the vehicle (e.g. ‘Eco’, ‘Maximum range’, ‘Comfort’ or ‘Sports’ mode), the operating mode being associated with a relative power consumption of the vehicle. A target cabin temperature is determined 306 by the processor(s) in dependence on the input data and the operating mode signal, and a control signal indicative of at least the target cabin temperature is output 308 by the processor(s) to control a heating, ventilation, and air conditioning (HVAC) system of the vehicle. A predicted mean vote thermal comfort model may be used to determine the target cabin temperature.

Description

TECHNICAL FIELD The present disclosure relates to determining a target cabin temperature for a heating, ventilation and air-conditioning (HVAC) system of a battery electric vehicle. Aspects of the invention relate to a control system, a vehicle system, a vehicle, and a method. BACKGROUND It is known to control a HVAC system of a battery electric vehicle according to a user-selected temperature preference. Such HVAC systems can also be controlled to reduce energy consumption where it is desirable to increase the range of the vehicle. For example, when a vehicle is in an “eco” or “maximum range” mode, an air temperature and / or fan speed of the HVAC system may be lowered to reduce energy consumption. It is an aim of the present invention to address one or more of the disadvantages associated with the prior art. SUMMARY OF THE INVENTION Aspects and embodiments of the invention provide a control system, a vehicle system, a vehicle, and a method, as claimed in the appended claims According to an aspect of the present invention there is provided a control system for a battery electric vehicle, the control system comprising one or more processors collectively configured to: receive input data indicative of: one or more user body-related parameters; and one or more environmental parameters; receive an operating mode signal indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle; in dependence on the input data and the operating mode signal, determine a target cabin temperature; and output a control signal indicative of at least the target cabin temperature, for controlling a heating, ventilation, and air conditioning (HVAC) system of the vehicle. By determining the control signal in this manner, energy consumption of the HVAC system may be reduced as appropriate for the current operating mode of the vehicle. Optionally, the one or more processors can be collectively configured to determine the target cabin temperature based at least in part on a thermal comfort model. The use of a thermal comfort model may provide improved subjective comfort and / or allow for reduced energy consumption. Optionally, the thermal comfort model can be a predicted mean vote (PMV) thermal comfort model, and the one or more processors can be collectively configured to: determine a PMV parameter based at least in part on the operating mode signal; and determine the target cabin temperature based at least in part on the thermal comfort model, at least partly in dependence on the PMV parameter. Optionally, the PMV parameter can comprise a PMV offset. Such an offset can be directional (e.g., can take a positive or negative value), or can be an absolute value the direction of which is implied by the operating mode of the HVAC system. Alternatively, the PMV parameter can be a PMV value rather than an offset. Optionally, the one or more processors can be collectively configured to: receive a cabin temperature parameter indicative of a user temperature preference; determine a first temperature at least partly in dependence on the input data and the PMV parameter; and adjust, at least partly in dependence on at least the cabin temperature parameter, the first temperature, thereby to determine the target cabin temperature. Optionally, the one or more processors can be collectively configured to: determine a temperature offset at least partly in dependence on the cabin temperature parameter; and adjust the first temperature by applying the temperature offset to the first temperature. Optionally, the one or more processors can be collectively configured to determine the target cabin temperature such that the HVAC system operates at a lower average power when the operating mode signal is indicative of the vehicle being in a first mode indicative of lower relative power consumption of the vehicle. This may enable reduced HVAC energy consumption when the vehicle is in the first mode. Optionally, the one or more processors can be collectively configured to modify the first temperature to determine the target cabin temperature such that the HVAC system is permitted to operate at a higher average power when the operating mode signal is indicative of the vehicle being in a second mode indicative of a higher relative power consumption of the vehicle. Permitting increased HVAC energy consumption may result in increased user comfort. Optionally, the operating mode signal can be indicative of an operating mode selected by the user. This may enable improved user control of the HVAC system, allowing an at least partly user-determined compromise between user comfort and vehicle energy consumption. Optionally, the operating mode signal can be indicative of an operating mode selected automatically by a system of the vehicle based at least in part on a predicted range of the vehicle. This may enable improved vehicle control of the HVAC system, allowing an at least partly vehicle-determined compromise between user comfort and vehicle energy consumption. Optionally, the operating mode signal can be indicative of an operating mode selected based on an outcome of a comparison between a predicted range of the vehicle and a distance to a destination currently selected within a navigation system of the vehicle. This may enable improved range management. Optionally, the one or more user body-related parameters can include: a metabolic parameter associated with at least one user in the vehicle; and / or a clothing parameter associated with at least one user in the cabin. Optionally, the one or more environmental parameters can comprise: an ambient temperature signal indicative of a temperature outside the vehicle; a mean radiant temperature parameter indicative of a mean radiant temperature of at least one surface within the cabin; a flow rate parameter, the flow rate parameter being indicative of a mass air flow rate of the HVAC system; a solar radiation parameter, the solar radiation parameter being indicative of an amount of solar radiation entering the cabin; and / or a relative humidity parameter, the relative humidity parameter being indicative of a relative humidity of air within the cabin. The control system comprises one or more controllers collectively comprising at least one electronic processor having an electrical input for receiving an input signal; and at least one memory device electrically coupled to the at least one electronic processor and having instructions stored therein; wherein the at least one electronic processor is configured to access the at least one memory device and execute the instructions thereon so as to: receive input data indicative of: one or more user body-related parameters; and one or more environmental parameters; receive an operating mode signal indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle; in dependence on the input data and the operating mode signal, determine a target cabin temperature; and output a control signal indicative of at least the target cabin temperature, for controlling a heating, ventilation, and air conditioning (HVAC) system of the vehicle. According to another aspect of the present invention, there is provided a vehicle system comprising: the control system of the preceding aspect; one or more sensors operatively connected to the control system, the one or more sensors being for generating the one or more user body-related parameters and / or the one or more environmental parameters and providing them to the control system; and an HVAC system operatively connected for receiving the control signal from the control system. According to another aspect of the present invention, there is provided a vehicle comprising the vehicle system of the preceding aspect, or the control system of the first aspect. According to another aspect of the present invention, there is provided a method for controlling an HVAC system of a vehicle, the method comprising: receiving input data indicative of: one or more user body-related parameters; and one or more environmental parameters; receiving an operating mode signal, the operating mode signal being indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle; determining a target cabin temperature, in dependence on the input data and the operating mode signal; and outputting a control signal to control the HVAC system, the control signal being indicative of at least the target cabin temperature. According to another aspect of the present invention, there are provided computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the method according to the preceding aspect. Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and / or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all embodiments and / or features of any embodiment can be combined in any way and / or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and / or incorporate any feature of any other claim although not originally claimed in that manner. BRIEF DESCRIPTION OF THE DRAWINGS One or more embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 shows a perspective view of a vehicle according to an embodiment of the invention; Figure 2 is a schematic view of the vehicle of Figure 1, comprising a control system according to an embodiment of the invention; Figure 3 shows a Predicted Mean Vote (PMV) graph; Figure 4 is schematic view showing modules implemented by a control system, according to an embodiment of the invention; Figure 5 is schematic view showing a control system and inputs, according to an embodiment of the invention; Figure 6 is schematic view showing modules implemented by a control system, according to an embodiment of the invention; and Figure 7 shows a method according to an embodiment of the invention. DETAILED DESCRIPTION A control system in accordance with an embodiment of the present invention is described herein with reference to the accompanying Figures. With reference to Figures 1 and 2, there is illustrated a control system 100 installed in a vehicle 200. The vehicle 200 is a battery electric vehicle, comprising a battery 202. The battery 202 is coupled to an inverter 204 that provides a drive current to an electric machine 206 as required, which in turn drives wheels 208 of the vehicle 200. The electric machine 206 can be the sole prime mover of the vehicle 200, or can be coupled to cooperate with another prime mover such as a diesel or petrol engine (not shown). The electric machine 206 and inverter 204 can optionally be operated in a regeneration mode, in which kinetic energy of the vehicle 200 is converted into electrical energy when braking is required, the electrical energy being used to recharge the battery 202. The control system 100 comprises one or more controller 102. The control system 100 is configured to receive input data 104 and an operating mode signal 106. As described in more detail below, the input data 104 includes one or more user body-related parameters. The user body-related parameters relate to user-specific factors associated with the heat generated and / or retained by a user’s body, for a user located within the vehicle. Non-limiting examples of user body-related parameters include a metabolic rate associated with one or more users, and a clothing parameter associated with clothing worn by one or more users. Examples of user body-related parameters, and the sensors, transducers, other hardware for providing such parameters, are described in more detail below. As described in more detail below, the input data 104 also includes one or more user environmental parameters. The environmental parameters relate to the environment surrounding one or more users, including within the cabin and / or outside the vehicle. Non-limiting examples of environmental parameters include an ambient temperature (e.g., the air temperature outside the vehicle), a radiant temperature associated with one or more surfaces within the cabin, an air mass flow rate of a heating, ventilation, and air conditioning (HVAC) system of the vehicle, solar radiation, and relative humidity. Examples of environmental parameters, and the sensors, transducers, other hardware for providing such parameters, are described in more detail below. The operating mode signal 106 is indicative of a current operating mode of the vehicle 200, the operating mode being associated with a relative power consumption of the vehicle 200. For example, the operating mode signal can indicate whether the vehicle is in a relatively low power mode, such as an “Eco” or “Maximum Range’’ mode, or in a relatively high power mode, such as a “Comfort” or “Sports” mode where range is of less relative importance. Further examples of such modes are described in more detail below. The control system 100 is configured to, in dependence on the input data 104 and the operating mode signal 106, determine a target cabin temperature. The control system 100 outputs a control signal 108 indicative of at least the target cabin temperature. The control signal 108 is provided as an input to an HVAC system 110 of the vehicle 200. Although a single target temperature is described below, it will be appreciated that in some embodiments, the vehicle will have two or more zones (e.g., driver and passenger, or driver, passenger, and rear seats) to which different target temperatures may apply. In such cases, the principles described in relation to the embodiments below can be applied to one or more of the zones. Optionally, the principles can be applied to only a true subset of such zones. For example, any of the embodiments below can be applied to a zone in which the driver sits, while the temperature(s) of other zone(s) in the vehicle is / are controlled in accordance with known temperature control principles. The HVAC system 110 is configured to heat or cool the cabin in accordance with known principles. For example, the HVAC system can include a controller (not shown) that controls the temperature of air supplied through one or more vents (not shown) within the cabin of the vehicle 200. The air temperature within the cabin can be modified by controlling the supply air temperature and the mass airflow rate, either or both of which can be selected by the user or set automatically by the HVAC system. A lower airflow rate may require a higher temperature to achieve the same target cabin temperature, particularly if the ambient temperature is very hot or cold and / or there is a desire to reach the target cabin temperature quickly. The HVAC controller can operate based on known control schemes, including proportional, integral, and / or differential control schemes, and / or fuzzy logic control schemes, such as those known in the art. The control system 100 as illustrated in Figure 2 comprises one controller 102, although it will be appreciated that this is merely illustrative. The controller 102 comprises processing means 114 and memory means 116. The processing means 114 may be one or more electronic processing device 114 which operably executes computer-readable instructions. The memory means 116 may be one or more memory device 116. The memory means 116 is electrically coupled to the processing means 114. The memory means 116 is configured to store instructions, and the processing means 114 is configured to access the memory means 116 and execute the instructions stored thereon. The controller 102 comprises an input means 118 and an output means 120. The input means 118 may comprise an electrical input 118 of the controller 102. The output means 120 may comprise an electrical output 120 of the controller 102. The input 118 is arranged to receive the input data 104 and the operating mode signal 106, as described above. The input data 104 is an electrical signal that is indicative of one or more user body-related parameters and one or more environmental parameters, as described above. The operating mode signal 106 is an electrical signal that is indicative of an operating mode of the vehicle 200, as described above. The output 120 is arranged to output the control signal 108 that is indicative of a target cabin temperature for controlling the HVAC system 110. The one or more processors can collectively be configured to determine the target cabin temperature based at least in part on a thermal comfort model. Thermal comfort models are based on human perception of the thermal environment, and are based on the subjective responses of experimental subjects. The human body generates heat as a result of respiration, and loses it to the surrounding environment dependent upon various factors such as air temperature, mass airflow, humidity, etc. Thermal comfort is a subjective perception arising at least partly out of net heat gains and losses. One thermal comfort model is the Predicted Mean Vote, PMV, model, based on Ranger's equations. Values of factors such metabolic rate, clothing insulation, air temperature, mean radiant temperature, air speed and relative humidity are used as inputs. Based on those inputs, the model outputs a PMV value that is indicative of the likely thermal comfort that will be experienced by a human experiencing a scenario corresponding to those inputs. Figure 3 shows a graph that illustrates how the PMV value is interpreted. The X-axis shows possible values of PMV from -3 to +3. The Y-axis shows a predicted percentage of people who will be dissatisfied (in the sense of feeling thermally uncomfortable) for a given PMV value. A PMV value of -3 predicts that 100% of the population will be dissatisfied due to feeling too cold. A PMV value of +3 predicts that 100% of the population will be dissatisfied due to feeling too hot. A PMV value of 0 predicts a point at which the fewest within a population will be dissatisfied. A PMV value of 0 still predicts that a small percentage of the population - 5%, say - will be dissatisfied. This may be due to individual thermal preferences, medical conditions that change thermal perception, or a number of other factors known to the skilled person. It will be appreciated that other thermal comfort models can be used. Examples include the Equivalent Homogenous Temperature (“EHT”) model defined in the ISO 7730:2005 standard (see Adaptive Models (see, for example, the Berkeley Model (see, for example, https:Vescholarship.o;'q / uc / item / 2tm289vb), and variants of the standard PMV model (see, for example, https: / / ww.sciQncedirectcorn / science / article / a^^ and The skilled person will be familiar with the adjustments needed to implement such alternative thermal comfort models in different embodiments of the invention. Figure 4 shows a schematic diagram of an embodiment of the invention in which a PMV thermal comfort model is implemented by the control system 100. Figure 4 shows functional modules implemented in software and / or hardware within the control system 100. A temperature determining module 122 accepts as an input the input data 104. A PMV determining module 124 accepts as an input the operating mode signal 106 and outputs a PMV parameter 126. The PMV parameter 126 is supplied as an input to the temperature determining module 122. The PMV parameter 126 can take the form of a PMV value. While the PMV thermal comfort model allows for PMV values ranging from -3 to +3, the PMV parameter will typically fall within a subset of that range, because it is unlikely to be acceptable that the cabin be so hot or cold as to be very uncomfortable. The PMV values output by the PMV determining module 124 can therefore selected from within a range such as -1 to +1, or more preferably -0.5 to +0.5. The range can be selected to suit particular implementation requirements. The range can also be adjusted to suit different regional and cultural preferences, which can be determined empirically. For example, for a particular model of vehicle, the range in one country can be, say, -0.5 to +0.7, and -0.25 to +0.25 in a country having different typical comfort preferences. The PMV parameter 126 can alternatively take the form of a PMV offset. In that case, the temperature determining module 122 has a default PMV value (typically PMV = 0), and the temperature determining module 122 applies the PMV offset to the default PMV value to produce a net PMV value that is used to determine the cabin target temperature, as described in more detail below. The PMV offset can be a signed value, in which case it can be added to the default PMV value to produce the net PMV value. Since the aim of the PMV offset is to reduce energy consumption of the HVAC system 110 when the vehicle is in a relatively low-power operating mode, the sign of the offset will depend on whether heating or cooling is required. For example, where the ambient temperature is relatively cold and the cabin is to be heated, energy consumption will be reduced if the target temperature is reduced. To achieve this, the net PMV value is reduced, which requires a negative PMV offset. Correspondingly, where the ambient temperature is relatively warm and the cabin is to be cooled, energy consumption will be reduced if the target temperature is increased. To achieve this, the net PMV value is increased, which requires a positive PMV offset. Alternatively, the PMV offset can be an unsigned value. In that case, the PMV offset is either added to, or subtracted from, the default PMV value to produce the new PMV value. The PMV offset is added to the default PMV value if the ambient temperature is relatively warm and the cabin is to be cooled, and subtracted from the default PMV value if the ambient temperature is relatively cold and the cabin is to be warmed. As mentioned above, the operating mode signal 106 can be indicative of an operating mode of the vehicle 200. The vehicle 200 can be operable in two more operating modes. For example, the vehicle 200 may be operable in an ordinary or “Comfort" operating mode, in which settings for vehicle systems such as the HVAC, battery regeneration, and acceleration are selected for increased passenger comfort. In many cases, settings that improve passenger comfort may increase average power consumption, which has a negative impact on vehicle range. The vehicle 200 may also be operable in an “Eco” mode, in which settings for vehicle systems are selected to provide a compromise between passenger comfort and vehicle range. The vehicle 200 may also be operable in a “Maximum Range” mode, in which settings for vehicle systems are selected to minimise energy consumption in order to maximise range. It will be appreciated that the vehicle can offer any number of operating modes, at least some of which will be associated with different relative power consumptions. The operating mode of the vehicle can be set in any suitable manner. For example, the operating mode may be selected by the user by way of a control interface (not shown). The control interface can be a touchscreen, one or more dials, buttons, sliders, or the like, or any other human-machine interface allowing the user to select the desired operating mode. Alternatively, the control interface can be provided by any app or other interface provided on a wireless device such as a mobile / cellular phone or tablet device. Such devices can communicate directly with a wireless interface offered by the vehicle, such as a wireless LAN, Bluetooth®, or other wireless protocol, or can communicate via a cellular or other network via which the vehicle can communicate. Alternatively, or in addition, the operating mode can be selected automatically by the vehicle 200. For example, the control system 100 can select an appropriate operating mode based at least in part on a predicted range of the vehicle 200. The predicted range can be determined in any suitable manner, as known to the skilled person. The predicted range can be used in conjunction with a distance to an intended destination. For example, a local or remote satellite navigation system (not shown) can be used to determine a distance to an intended destination, and to estimate the energy consumption of the vehicle to reach that destination. By comparing the distance to the destination with the predicted range of the vehicle, a suitable operating mode can be selected without the need for user input. For example, if the predicted range will not allow a sufficient margin of safety given the intended destination, an operating mode offering lower energy consumption may be selected. If there is ample range, an operating mode offering a higher energy consumption may be selected. In other embodiments, the operating mode of the vehicle is not selected from a small number of possible modes (e.g., “Comfort”, “Eco”, and “Maximum Range”). Instead, the vehicle can be configured to select settings for individual vehicle systems or groups of systems in a more granular manner. For example the PMV controller can interact with an intelligent power mode system. Such a system is designed to control operation of individual vehicle systems and groups of systems based on the battery state of charge. In such an arrangement, there are as many “operating modes” as there are parameter combinations for vehicle systems or groups of systems that can be controlled based on power consumption. User preferences can be taken into account when determining the settings for the vehicle systems and / or groups of systems. For example, a particular user may prefer not to use strong regenerative braking, and so this setting will not be selected unless absolutely necessary to meet range or power consumption requirements based on the current state of charge and / or intended destination. The control system 100 determines the PMV parameter 126 based at least in part on the operating mode signal 106. This can involve, for example, using a lookup table of potential mappings between the operating mode signal 106 and the PMV parameter 126. As an example, for a vehicle having “Comfort”, “Eco”, and “Maximum Range” vehicle operating modes, and where the PMV parameter 126 is the PMV value, the following lookup table can be used: Vehicle Operating Mode PMV Comfort A Eco B Maximum Range C The values of A, B, and C can be selected to suit the particular implementation requirements. For example, ‘A’ may take a value of 0. Since the vehicle is in Comfort mode, energy consumption is considered relatively unimportant, and so the target temperature is be selected to maximise user comfort (which happens at PMV=0). ‘B’ may take a value of 0.25, and ‘C’ may take a value of 0.5, representing sequentially reducing average energy consumption as the operating mode moves in the direction of increasing range. The PIW values in the table can all be positive, as described above, in which case the temperature determining module needs to determine whether to use the PMV value as-is (as would be needed in the event the cabin is being cooled), or to first negate the PMV value (as would be needed in the event the cabin is being heated). Alternatively, the PMV determining module can itself output a positive or negative PMV value depending upon whether cooling or heating is required. Whether heating or cooling will be required can be determined by comparing the ambient temperature with a user-selected (or preset) cabin temperature. For example, if the ambient temperature is higher than the selected cabin temperature, then heating mode is enabled, and if the ambient temperature is lower than the selected cabin temperature, then cooling mode is enabled. In yet other embodiments, the PMV parameter can be a PMV offset. In that case, a default PMV value is modified based on the PMV offset. Where used, the default PMV value can be stored by the PMV determining module 124 or the temperature determining module 122. Typically, the PMV offset will be applied to the default PMV value by the module that stores the default PMV value. Where the default PMV value is zero, the values of PMV offsets required to give particular PMV values after applying them to the default PMV value (=0) gives the same result as using the same offsets directly as PMV values. It is only when the default PMV value is non-zero that the result is different. Returning to Figure 4, the temperature determining module 122 determines the target cabin temperature based on the input data 104 and the PMV parameter 126. This can be achieved by solving a PMV model equation using those inputs. A specific example of a PMV model equation will now be described with reference to Figure 5, in which a specific set of input data 104 is shown. The skilled person will appreciate that, in other embodiments, a different set of input data 104 can be used. In Figure 5, the input data 104 includes user body-related parameters including: a metabolic parameter 128 associated with at least one user in the vehicle 200; and a clothing parameter 130 associated with at least one user in the cabin. A user having a higher or lower metabolic rate may find a higher or lower target cabin temperature acceptable, depending, for example, upon whether the HVAC system is heating or cooling the cabin. A user wearing more and / or more insulative clothing may similarly find a higher or lower target cabin temperature acceptable, depending, for example, upon whether the HVAC system is heating or cooling the cabin. The metabolic parameter 128 can be provided based on signals generated by one or more sensors 142. Such sensor(s) 142 can take any suitable form. For example, the sensor(s) 142 can include a camera that captures one or more images of at least one user within the cabin. The one or more images can be analysed to determine one or more factors related to the likely metabolism of the user. For example, the gender of the user, the size or weight of the user, and / or an age of the user can be estimated based on the captured images, and predictions made about the likely metabolic rate of the user. For example, on average, men will tend to generate more energy than women, larger / heavier people will tend to generate more energy than smaller / lighter people, and the elderly and very young will tend to generate less energy than those of other ages. Other sensor(s) 142 can be used. For example, the weight of a user can be estimated by way of a seat pad mass sensor (not shown). Alternatively, or in addition, a skin temperature of one or more users can be estimated, for example by using an infrared, laser, or other temperature sensor (not shown). The metabolic parameter 128 can also vary depending upon whether the user for which the parameter is being generated is driving, because, in general, the driver will have a slightly higher metabolism than other passengers who are not driving. The clothing parameters 130 can be provided based on signals generated by one or more sensors 144. Such sensor(s) 144 can take any suitable form. For example, the sensor(s) 144 can include a camera that captures one or more images of at least one user. The one or more images can be analysed to determine one or more factors related to the clothing likely to be worn by at least one user. For example, if the user is wearing a heavy coat, they will tend to retain more heat, and hence will require less heating (i.e., if the ambient temperature is cold), or more cooling (i.e., if the ambient temperature is hot). The analysis can include factors such as the amount of the user’s body that is covered by clothing, the type of clothing (including fabric type and thickness), and / or the number of layers of clothing. Alternatively, or in addition, the clothing parameter 130 can be at least partly estimated based on the ambient temperature. For example, if the ambient temperature is low, it may be predicted that the user will be wearing warm clothing, and the clothing parameter 130 can be modified accordingly. This may reduce the amount of processing required, as compared with determining the clothing parameter based on what the user is actually wearing. The metabolic parameters 128 and / or the clothing parameters 130 can be predicted or estimated at least partly based on Al analysis of images or other data captured by the sensors 142, 144. Such analysis is known to the skilled person, and will not be described in more detail here. The sensors 144 can be separate from the sensors 142. Alternatively, at least some of the sensors 142, 144 can be the same. For example, a single camera can be used to provide one or more images, at least partly based upon which the metabolic parameters 128 and clothing parameters 130 are generated. The input data 104 also includes environmental parameters including: an ambient temperature signal 132 indicative of a temperature outside the vehicle; a mean radiant temperature parameter 134 indicative of a mean radiant temperature of at least one surface within the cabin; a flow rate parameter 136 indicative of a mass airflow rate of the HVAC system.; a solar radiation parameter 138 indicative of an amount of solar radiation entering the cabin; and / or a relative humidity parameter 140 indicative of a relative humidity of air within the cabin. The ambient temperature signal 132 can be generated by a thermal sensor 146 positioned to sense the external air temperature. For example, the thermal sensor 146 can be located within a side mirror 148 of the vehicle 200, although any other suitable location may be used. To reduce the effect of localised temperature differences, several such thermal sensors 146 can be provided at different locations on the vehicle, and the sensed temperatures averaged. Where separate target temperatures are determined for different zones of the vehicle, the thermal sensor(s) local to the zone for each target temperature can be weighted more heavily than zones that are further away. Alternatively, or in addition, the ambient temperature signal 132 can be generated based on a local weather report or other temperature-related information, which can be retrieved via a wireless network such as a mobile telecommunications network. The mean radiant temperature parameter 134 can be generated based on the ambient temperature and the cabin temperature. For example, the mean radiant temperature 134 can be obtained by calculating an average of the ambient temperature and the cabin temperature. The average can be a weighted average, in which case weighting factors can be determined from computational simulations based on a suitable combination of one or more parameters, such as ambient temperature, solar irradiation (see below), vehicle speed, and / or cabin temperature. Alternatively, fixed weighting factors can be used, which allows for reduced data storage and processing requirements. In certain contexts, localized heating / cooling can be more effective for human comfort and energy efficiency. Including the impact of local surface heating / cooling, such as steering and / or seat heating, can therefore improve the outcome of modelling thermal comfort as well as potentially allowing a target temperature that offers reduced energy consumption for a given level of thermal comfort. Accordingly, heated or cooled contact surfaces within the cabin, such as a heated steering wheel and / or seat, can be treated separately within the PMV-based model. The standard PMV model uses a lumped mass model in which heat transfer to all body parts is treated equally. Conduction through a heated seat and / or steering wheel can be incorporated into the model by measuring the heat generated by those systems and applying a contact conduction coefficient for the parts of the body near or in contact with the seat and / or steering wheel, which increases the contribution of those heating types on thermal comfort. The conduction coefficient can optionally be applied in a way that takes into account clothing factors. A potential drawback with this approach is that it does not consider the sensitivity of different body parts to heat, and the corresponding impact on thermal comfort. To counter this, the Berkeley method for body part sensitivity can be employed. The human body is divided into parts, each of which is allocated a sensitivity to comfort based on temperature. Heat transfer is measured for each of these parts, and thermal comfort is summed across all body parts taking per-body-part sensitivity into account. The result is used in the original PMV equation as the heat transfer from conduction. In effect, this results in the model taking into account both contact / local conduction and the sensitivity of different body parts to thermal comfort. The flow rate parameter 136 can be supplied by the HVAC system 110, but other flow rate sensors (not shown) can be used in different implementations. Optionally, the air flow parameter 136 can take into account both fan speed (i.e. flow rate) and the position of one or more vents supplying the air. Computational fluid dynamics can be used to model the airflow parameter 136 for various fan speeds and positions during design and testing. The results can be provided in a lookup table or simplified interpolative model that can be run by the control system 100. The solar radiation parameter 138 can be provided based on signals generated by one or more sensors 152. Such sensor(s) 152 can take any suitable form. For example, the sensor(s) 152 can include a solar panel, light-dependent resistor, and / or any other light-sensitive device that can output an indication of the amount of solar radiation falling on it. Several such sensors 152 can be provided at different positions within the cabin to capture sunlight falling from different directions, and the outputs averaged. Where separate target temperatures are determined for different zones of the vehicle, the thermal sensor(s) local to the zone for each target temperature can be weighted more heavily than zones that are further away. Alternatively, or in addition, the solar radiation parameter 138 can be generated based on an insolation forecast, which can be retrieved via a wireless network such as a mobile telecommunications network. The direction in which the vehicle 200 is headed, and the estimated solar angle of incidence, can be used to model solar energy entering the vehicle 200, and CFD simulations can be used to estimate the resultant heat transfer to the body. The relative humidity parameter 140 can be provided based on signals generated by one or more sensors 154. Such sensor(s) can take any suitable form. For example, the sensor(s) 154 can form part of the HVAC system 110, in which case the relative humidity parameter can be provided by the HVAC system 110. Alternatively, one or more humidity sensors 154 can be positioned at one or more locations within the cabin, air inlets, and / or air outlets, for example. A typical PMV model takes various inputs and outputs a PMV value that indicates the predicted thermal comfort of the environment based on those inputs (see graph of Figure 3). A highly simplified equation for a PMV model therefore has the form: fpMv(inputs) = PMV where fpMv is the PMV model function. As explained above, the inputs of the PMV model include user body-related parameters and environmental parameters. In a typical PMV model, air temperature is one of the environmental parameters. The equation above can be rearranged as follows: fpMv’(PMV, inputs other than air temperature) = air temperature where fpMv’ is the PMV model function rearranged to accept PMV as one of the inputs, and to output air temperature. The air temperature is the target air temperature of which the control signal 108 is indicative. Control signal 108 is output by output means 120 for use by the HVAC system 110 in setting operating parameters such as fan speed and air temperature, e.g. as described above. A further embodiment will now be described with reference to Figure 6. The embodiment of Figure 6 shares several elements with previously described embodiments, and like elements are indicated with the same reference signs. Figure 6 shows a schematic diagram of an embodiment of the invention in which a PMV thermal comfort model is implemented by the control system 100. Figure 6 shows functional modules implemented in software and / or hardware within the control system 100. In the embodiment of Figure 6, the first temperature determining module 122 is configured to determine a first temperature 156 at least partly in dependence on the input data 104 and the PMV parameter 126, for example as described above with reference to the embodiment of Figure 4. The first temperature 156 is supplied as an input to a temperature adjustment module 158. The temperature adjustment module 158 is also configured to receive a cabin temperature parameter 160 indicative of a user temperature preference. The cabin temperature parameter 160 can be based on user interaction with a user interface 162, which can include, for example, HVAC controls. The user interface 162 can include a touchscreen, one or more dials, buttons, sliders, or the like, or any other human-machine interface allowing the user to select a preferred cabin temperature. The temperature can be selected in degrees Celsius or Fahrenheit, for example, depending upon local standards and / or user preference, or can be represented graphically by a colour (e.g., blue for cold, red for hot, and shades of purple for intermediate temperatures) and / or a graphical indicator (e.g., the position of an indicator on a dial, the size of a linear bar, or the like, indicating a selection within a range of possible cabin temperatures). Alternatively, the cabin temperature parameter 160 can be stored in the memory means 116 (or remotely, accessible by way of a wireless telecommunications network, for example). The cabin temperature parameter 160 can be stored for the vehicle, or for one or more particular users. For example, the control system 100 may store (again, locally or remotely) a profile for one or more users. Each profile can include at least one preferred cabin temperature upon which the cabin temperature parameter 160 can be based. Alternatively, different cabin temperatures can be stored depending upon whether the HVAC system 110 is in cooling or heating mode. The temperature adjustment module 158 is configured to adjust the first temperature 156 in dependence on the cabin temperature parameter 160, to generate the cabin target temperature. For example, if the first temperature 156 is different to the temperature indicated by the cabin temperature parameter 160, then the first temperature 156 can be adjusted in the direction of the cabin temperature parameter 160. For example, the temperature adjustment module 158 can determine a temperature offset at least partly in dependence on the cabin temperature parameter 160, and adjust the first temperature 156 by applying the temperature offset to the first temperature 156. Such a temperature offset can be determined in any suitable manner, such as by applying a function to a difference between the first temperature 156 and the cabin temperature parameter 160. For example, the temperature offset can be half of the difference between the first temperature 156 and the cabin temperature parameter 160 (which is mathematically equivalent to averaging the two values). A proportion other than 50% may be used, and any such proportion can vary depending on the magnitude of the difference. In other implementations, a non-linear function, such as a quadratic function, can be used to determine the temperature offset. Any function used in determining the temperature offset can optionally be selected to suit different regional and cultural preferences, which can be determined empirically. For example, for a particular model of vehicle, a 30% proportion can be used in one country, and a 50% proportion can be used in another country. In the embodiments described above, the controller 100 is configured to determine the target cabin temperature such that the HVAC system 110 operates at a lower average power when the operating mode signal is indicative of the vehicle 200 being in a first mode indicative of lower relative power consumption of the vehicle 200. In the example where vehicle 200 has Comfort, Eco, and Maximum Range operating modes, when Maximum Range mode is selected, the target cabin temperature is reduced (when in heating mode), which results in lower energy consumption. Optionally, when Eco mode is selected, the target cabin temperature is reduced (when in heating mode) by less than when in the Maximum Range mode. When Comfort mode is selected, the target cabin temperature need not be reduced. Similar comments apply when in cooling mode, except that the target cabin temperature will be increased. In the embodiments described above, the controller 100 is also configured to determine the target cabin temperature such that the HVAC system 110 is permitted to operate at a higher average power when the operating mode signal is indicative of the vehicle 200 being in a second mode indicative of a higher relative power consumption of the vehicle 200. In the example where vehicle 200 has Comfort, Eco, and Maximum Range operating modes, when Comfort Mode is selected, the target cabin temperature is not reduced (when in heating mode), which permits the HVAC system 110 to consume more energy if needed to maintain the target cabin temperature. Similar comments apply when in cooling mode, except that the target cabin temperature will be increased. In alternative embodiments, the contribution of heated or cooled contact surfaces, such as heated steering and / or seats, is not modelled within the PMV-based model. Instead, based on the use of heated / cooled contact surfaces, a further correction factor is applied to the target temperature before supplying it to the HVAC system. For example, when the vehicle is in a heating mode, the target temperature can be reduced if the steering wheel and / or seats are being heated. Optionally, the temperature or relative heat setting of the steering wheel and / or seats can be taken into account, such that the target temperature is lowered by a greater amount for increasing contact surface temperature. Optionally, the target temperature is lowered by a greater amount when both steering wheel and seats are being heated, as compared with only the steering wheel or the seats. Optionally, a weighting factor can be applied. For example, seat heating may contribute more to thermal comfort than steering wheel heating, meaning that the target temperature may be reduced more as a result of seat heating than steering wheel heating. This may, however, be dependent on relative temperatures of the steering wheel and seat(s), cultural and regional preferences, and the difference between cabin and ambient temperatures, for example. Figure 7 illustrates a method 300 according to an embodiment of the invention. The method 300 is a method of controlling an HVAC system of a vehicle, such as the HVAC system 110 of the vehicle 200 illustrated in Figures 1 and 2. The method 300 may be performed by the control system 100 illustrated in Figure 2, for example. In particular, the memory 116 may comprise computer-readable instructions that, when executed by the processor 114, perform the method 300 according to an embodiment of the invention. Method 300 comprises: receiving 302 input data indicative of one or more user body-related parameters and one or more environmental parameters; receiving 304 an operating mode signal, the operating mode signal being indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle; determining 306 a control signal comprising at least a target cabin temperature, in dependence on the input data and the operating mode signal; and outputting 308 the control signal to control the HVAC system. A specific set of PMV-based equations will now be described for a specific implementation. It will be appreciated that parameters and values in these equations represent only a single embodiment, and can be varied as needed to suit different implementation requirements. PMV can be defined as: PMV = Tst(Mnet— Htot) where: Tst = (0.303e-°O36Mnet + 0.028) Htot - Hdiff + Hsw + Hresp.lat + Hresp.dry + Hrad + Hconv- Qsolar Hdiff = 3.05(0.001)(5733 - 6.99(Mnet) -10(RH) e16'^36~r^^ Heat loss by diffusion Hsw - 0.42(Mnet — 58.15) -> Heat Loss due to sweating Hresp.iat = 1.7(0.00001)(5867 - 10(RH) e16'6536 4030.183 Tair,c+235)(Mnet) -> Heat transfer due to respiration Hresp.dry = 0.0014(34 - Tar,c)(Mnet) -> Dry Heat transfer due to respiration Hradiation = 3.96(Fd)((—)4 - (^1^)4) Radiative Heat transfer \ Ml 10() / \ 10() 7 7 Hconvection = (Fci)(hc)(Tci.o-Tair.c) ~Convective Heat Transfer In addition: 6536 4030A83_. pa = RH * 10 * e{ ‘ 7^,-+235-1 Ts = 0.303 * e-00036.Mnet + 0.0028 Tcl = 35.7 - 0.028 * (Mnet (3.96 * 10-8 * Fei((tei + 273)4 - (MRT + 273)4)) + Fcl * hc * (Td ~ Tair) 2.38 * |K, - Tair\°'25 for 2.38 * \Tcl - Tair\023 > 12.1 * 12.1 * for 2.38 *   - W25 < 12.1 * jva f 1 + 1.29 * 7ci for 23Q^\Tcl-Tair\025> 12.1 (1.05 + 0.645 * Icl for 2.38 * |Td - Tair\025 < 12.1 * PMV = Ts(Mnet - (3.05 * 0.001 * (5733 - 6.99 * Mnet - Pa) + (0.42 * (Mnet - 58.15)) + (0.00017 * (5867 - pa )) + (0.0014 * (34 - Tair) * Mnef) / ((Td \4 (MRT\4\ \ , + I 3.96 * Fcl * H —) - ) I + (Fcl * hc * (Tcl ~ Tair)) ~ Qsolar) Where: ^net = Metabolic rate (\Nlm2) Icl = Clothing insulation (m2 / K*W) Fci = Clothing surf ace area factor Tatr = Target air temperature (°C) MRT = Mean radiant temperature (°C) Va = Air velocity (m / s) Pa = Water vapour partial pressure (Pa) Hc = Convective heat coefficient (W / m2*K) Tcl = Clothing surface temperature (°C) RH = Relative humidity (%) PMV = PMV target Qsoiar = Solar radiation incident on passenger (W / m2) Rearranging the expression for PMV to solve for Tair : , + c + jT ) air (0.0014*Mnei+ Fc]*hc) where: C = (3.05 * 0.001 * (5733 - 6.99 * Mnet - pa) + (0.42 * (Mnet - 58.15)) + (0.00017 * (5867 - pa )) + (0.0014 * (34) * Mnet) + ^3.96 * Fcl *        - (7^)    + (^ct *hc* (Tci )) - Qsoiar The skilled person will observe that there are a number of differences in the above as compared with a standard PMV implementation. For example, humidity is used instead of saturation air pressure, and solar radiation is added. The skilled person will understand the ramifications of these changes, and so they are not described in greater detail. It will be appreciated that various changes and modifications can be made to the present invention without departing from the scope of the present application.

Claims

1. A control system for a battery electric vehicle, the control system comprising one or more processors collectively configured to:receive input data indicative of:one or more user body-related parameters; andone or more environmental parameters;receive an operating mode signal indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle;in dependence on the input data and the operating mode signal, determine a target cabin temperature; andoutput a control signal indicative of at least the target cabin temperature, for controlling a heating, ventilation, and air conditioning system of the vehicle.

2. The control system of claim 1, wherein the one or more processors are collectively configured to determine the target cabin temperature based at least in part on a thermal comfort model.

3. The control system of claim 2, wherein the thermal comfort model is a predicted mean vote thermal comfort model, and the one or more processors are collectively configured to:determine a PMV parameter based at least in part on the operating mode signal; anddetermine the target cabin temperature based at least in part on the thermal comfort model, at least partly in dependence on the PMV parameter.

4. The control system of claim 3, wherein the PMV parameter comprises a PMV offset.

5. The control system of claim 3 or 4, wherein the one or more processors are collectively configured to:receive a cabin temperature parameter indicative of a user temperature preference;determine a first temperature at least partly in dependence on the input data and the PMV parameter; andadjust, at least partly in dependence on at least the cabin temperature parameter, the first temperature, thereby to determine the target cabin temperature.

6. The control system of claim 5, wherein the one or more processors are collectively configured to: determine a temperature offset at least partly in dependence on the cabin temperature parameter; and adjust the first temperature by applying the temperature offset to the first temperature.

7. The control system of any preceding claim, wherein the one or more processors are collectively configured to determine the target cabin temperature such that the HVAC system operates at a lower average power when the operating mode signal is indicative of the vehicle being in a first mode indicative of lower relative power consumption of the vehicle.

8. The control system of any preceding claim, wherein the one or more processors are collectively configured to modify the first temperature to determine the target cabin temperature such that the HVAC system is permitted to operate at a higher average power when the operating mode signal is indicative of the vehicle being in a second mode indicative of a higher relative power consumption of the vehicle.

9. The control system of any preceding claim, wherein the operating mode signal is indicative of an operating mode selected by the user.

10. The control system of claim 9, wherein the operating mode signal is indicative of an operating mode selected based on an outcome of a comparison between a predicted range of the vehicle and a distance to a destination currently selected within a navigation system of the vehicle.

11. The control system of any preceding claim, wherein the one or more user body-related parameters include: a metabolic parameter associated with at least one user in the vehicle; and / or a clothing parameter associated with at least one user in the cabin.

12. The control system of any preceding claim, wherein the one or more environmental parameters comprise:an ambient temperature signal indicative of a temperature outside the vehicle;a mean radiant temperature parameter indicative of a mean radiant temperature of at least one surface within the cabin;a flow rate parameter indicative of a mass air flow rate of the HVAC system;a solar radiation parameter indicative of an amount of solar radiation entering the cabin; and / ora relative humidity parameter indicative of a relative humidity of air within the cabin.

13. A vehicle system comprising:the control system of any preceding claim;one or more sensors operatively connected to the control system, the one or more sensors being for generating the one or more user body-related parameters and / or the one or more environmental parameters and providing them to the control system; andan HVAC system operatively connected for receiving the control signal from the control system.

14. A vehicle comprising the vehicle system of claim 13 or the control system of any one of claims 1 to 12.

15. A method for controlling an HVAC system of a vehicle, the method comprising:receiving input data indicative of:one or more user body-related parameters; andone or more environmental parameters;receiving an operating mode signal, the operating mode signal being indicative of a current operating mode of the vehicle, the operating mode being associated with a relative power consumption of the vehicle;determining a target cabin temperature, in dependence on the input data and the operating mode signal; andoutputting a control signal to control the HVAC system, the control signal being indicative of at least the target cabin temperature.

Images