A heater power control method, system, storage medium and vehicle

Abstract

The application provides a heater power control method, system, storage medium and vehicle, the method comprising: obtaining the actual temperature of the heater, and calculating the current temperature deviation according to the target temperature and the actual temperature; wherein the target temperature is determined according to the input air conditioner adjustment request; monitoring the change trend of the actual temperature to identify that the temperature rise is close to the working condition or the temperature drop is close to the working condition; calculating the current temperature change rate of the actual temperature; determining the target proportional term negative gain basic coefficient under the current temperature deviation and the current temperature change rate based on the first mapping relationship; wherein the first mapping relationship is used to represent the corresponding proportional term negative gain basic coefficient under different temperature deviations and temperature change rates; determining the target proportional coefficient according to the target proportional term negative gain basic coefficient; and correcting the output power of the heater based on the target proportional coefficient. The application greatly improves the problems of temperature overshoot, overshoot and repeated oscillation, and improves the stability of temperature control.

Description

Technical Field

[0001] This application relates to the field of automotive thermal management technology, and in particular to a heater power control method, system, storage medium, and vehicle. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the vehicle's thermal management system plays a crucial role in ensuring passenger cabin comfort and the safe operation of the power battery. Currently, new energy vehicles typically use positive temperature coefficient heaters to heat the circulating water in the air conditioning system to provide the heat required for passenger cabin heating and battery thermal management. To ensure that the heater can provide the appropriate amount of heat as needed, the outlet water temperature of the heater needs to be precisely controlled.

[0003] However, related technologies often have a certain lag when performing thermal management, which can easily lead to phenomena such as overheating and repeated oscillations. Summary of the Invention

[0004] This application provides a heater power control method, system, storage medium, and vehicle to improve the temperature overshoot and oscillation problems caused by thermal inertia and hysteresis in the prior art.

[0005] This application provides a heater power control method, comprising: acquiring the actual temperature of the heater, and calculating a current temperature deviation based on a target temperature and the actual temperature; wherein the target temperature is determined based on an input air conditioning adjustment request; monitoring the change trend of the actual temperature to identify a heating-approaching condition or a cooling-approaching condition; wherein the heating-approaching condition is used to characterize that the heater temperature is lower than the target temperature and gradually approaches the target temperature; the cooling-approaching condition is used to characterize that the heater temperature is higher than the target temperature and gradually approaches the target temperature; calculating the current temperature change rate of the actual temperature; determining a target proportional term negative gain base coefficient based on the current temperature deviation and the current temperature change rate based on a first mapping relationship; wherein the first mapping relationship is used to characterize the proportional term negative gain base coefficient corresponding to different temperature deviations and temperature change rates, and the proportional term negative gain base coefficients corresponding to the heating-approaching condition and the cooling-approaching condition are different; determining a target proportional coefficient based on the target proportional term negative gain base coefficient; and correcting the heater output power based on the target proportional coefficient.

[0006] In one embodiment of this application, the step of calculating the current temperature change rate of the actual temperature includes: recording the trigger times of N consecutive monotonic temperature changes to form a time queue; wherein N is a positive integer greater than or equal to 3; and determining the real-time temperature change rate based on the time queue and the total time.

[0007] In one embodiment of this application, the step of determining the real-time temperature change rate based on the time queue and the total time includes: using the trigger times of multiple adjacent temperature changes with the same trend as flag bits based on the time queue, calculating the time interval between corresponding flag bits; and using multiple consecutive time intervals as the total time to calculate the real-time temperature change rate.

[0008] In one embodiment of this application, after determining the real-time temperature change rate based on the time queue and the total time, the method further includes: when a new temperature change is detected at the trigger time, updating the time queue so that the time queue always retains the most recent N trigger times; updating the real-time temperature change rate based on the updated time queue, and using the average of the real-time temperature change rates obtained by a preset number of updates as the final real-time temperature change rate.

[0009] In one embodiment of this application, the step of monitoring the actual temperature change trend to identify the heating approach condition or the cooling approach condition includes: if the temperature changes M times consecutively show an increasing trend and the actual temperature is less than the target temperature, then the current operating condition is determined to be the heating approach condition, where M is a positive integer greater than or equal to 3; if the temperature changes M times consecutively show a decreasing trend and the actual temperature is greater than the target temperature, then the current operating condition is determined to be the cooling approach condition.

[0010] In one embodiment of this application, the step of determining the target proportional coefficient based on the negative gain base coefficient of the target proportional term includes: determining a first correction value for the target temperature and the current air conditioner blower fan speed setting based on a second mapping relationship; wherein the second mapping relationship is used to characterize the proportional coefficient under different target temperatures and air conditioner blower fan speed settings; determining a second correction value for the deviation between the ambient temperature and the current temperature based on a third mapping relationship; wherein the third mapping relationship is used to characterize the proportional coefficient under different ambient temperatures and temperature deviations; and using the product of the first correction value, the second correction value, and the negative gain base coefficient of the target proportional term as the target proportional coefficient.

[0011] In one embodiment of this application, the step of correcting the output power of the heater based on the target proportionality coefficient includes: setting the target proportionality coefficient to a negative number when the temperature rises to near the operating condition, so as to reduce the output power of the heater in advance; and setting the target proportionality coefficient to a positive number when the temperature drops to near the operating condition, so as to increase the output power of the PTC heater in advance.

[0012] This application also provides a heater power control system, comprising: a temperature detection module for acquiring the actual temperature of the heater and calculating the current temperature deviation based on a target temperature and the actual temperature; wherein the target temperature is determined based on an input air conditioning adjustment request; a condition identification module for monitoring the changing trend of the actual temperature to identify a heating approach condition or a cooling approach condition; wherein the heating approach condition is used to characterize that the heater temperature is lower than the target temperature and gradually approaches the target temperature; the cooling approach condition is used to characterize that the heater temperature is higher than the target temperature and gradually approaches the target temperature; a base coefficient determination module for calculating the current temperature change rate of the actual temperature; determining a target proportional term negative gain base coefficient based on the current temperature deviation and the current temperature change rate; wherein the first mapping relationship is used to characterize the proportional term negative gain base coefficient corresponding to different temperature deviations and temperature change rates, and the proportional term negative gain base coefficients corresponding to the heating approach condition and the cooling approach condition are different; and a correction control module for determining a target proportional coefficient based on the target proportional term negative gain base coefficient; and correcting the output power of the heater based on the target proportional coefficient.

[0013] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the heater power control method described above. This application also provides a vehicle including the aforementioned heater power control system.

[0014] This application also provides a controller, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described heater power control method.

[0015] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described heater power control method.

[0016] The beneficial effects of this application are as follows: This application proposes a heater power control method, system, storage medium, and vehicle. By calculating the current temperature change rate of the actual temperature in real time and determining the target proportional term negative gain base coefficient based on the temperature deviation and temperature change rate, predictive reverse damping or compensation is introduced. This scheme changes the limitation of traditional control algorithms that rely solely on the current deviation for passive adjustment. It can detect the changing trend in advance and reduce or increase the output power when the temperature rapidly approaches the target value. This predictive adjustment cleverly utilizes the system's own thermal inertia, effectively reducing the probability of the actual water temperature exceeding the target temperature, greatly improving the problems of temperature overshoot, overshoot, and repeated oscillations, and enhancing the stability of temperature control. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0018] In the attached diagram: Figure 1 A schematic flowchart of a heater power control method provided in an embodiment of this application; Figure 2 This is a block diagram of a heater power control system provided in one embodiment of this application; Figure 3 This is a schematic diagram of an optional internal structure of the controller in one embodiment. Detailed Implementation

[0019] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0020] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0021] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0022] Most existing PTC water temperature control algorithms currently use the traditional PID (Proportional-Integral-Derivative) algorithm to control PTC power. This involves a combination of the P, I, and D terms, with the basic formula as follows:

[0023] Where u(k) is the final control power, Kp is the proportional coefficient, Ki is the integral coefficient, Kd is the derivative coefficient, and e(k) is the target water temperature minus the actual water temperature, which is the deviation value.

[0024] Option P increases the PTC power to rapidly raise the temperature based on the difference between the actual and target water temperatures. Option I compensates for small temperature differences by accumulating the deviation. When the actual water temperature is close to the target temperature, Option D reduces the power in advance to prevent overheating. Due to the non-linear relationship between the PTC water temperature rise trend and the heating power, this method of water temperature control often exhibits large inertia and lag, easily leading to overheating and repeated oscillations.

[0025] In the field of automotive thermal management technology, especially in the thermal management architecture of new energy vehicles, positive temperature coefficient (PTC) heaters are widely used to heat the circulating coolant, thereby exchanging heat with the passenger compartment air through the heater core, or providing heat to the power battery through plate heat exchangers. However, the water temperature control system is a typical nonlinear system with large hysteresis and large thermal inertia. Specifically, the PTC heating medium (such as antifreeze) and the circulation pipeline itself have a large specific heat capacity and mass. During the high-power heating stage, the input heat energy is not instantly and completely converted into a rise in water temperature, but a considerable amount of heat accumulates in the heating element and pipeline. When the temperature sensor detects that the actual water temperature is close to the target temperature and causes the traditional proportional-integral-derivative control algorithm to start reducing the output power, the previously accumulated excess heat continues to be released. This physical delay in heat release causes the actual water temperature to easily exceed the target temperature, resulting in overshoot and overshoot, which in turn causes repeated oscillations of temperature rise and fall.

[0026] Furthermore, the water temperature system is a typical nonlinear asymmetric system. Its heating process relies on an active heat source (PTC heater) to inject heat, resulting in rapid temperature rise and high thermal inertia; while the cooling process mainly relies on natural heat dissipation through the pipes or heat dissipation from external loads (such as the passenger compartment blower), resulting in a relatively slow cooling process and lower inertia. Traditional PID control algorithms typically use a fixed set of parameters to simultaneously address these two physically different processes of heating and cooling, easily leading to parameter interference and difficulty in achieving stable control under both operating conditions. Based on the above technical problems, this application provides a heater power control method, system, storage medium, and vehicle. By introducing a predictive incremental PI control architecture based on the temperature change rate and combining it with operating condition identification to decouple the heating and cooling processes, it effectively reduces the probability of the actual water temperature exceeding the target temperature and improves the problems of temperature overshoot, overshoot, and repeated oscillations. The technical solution of this application will be described in detail below with reference to specific embodiments.

[0027] In some embodiments, please refer to Figure 1 This application provides a heater power control method, which can be executed by a vehicle thermal management controller (such as an air conditioning controller or a vehicle controller). Of course, the specific executing entity can be configured and adjusted according to actual application requirements; this is merely an example. The method includes the following steps: Step S100: Obtain the actual temperature of the heater and calculate the current temperature deviation based on the target temperature and the actual temperature; wherein, the target temperature is determined based on the input air conditioning adjustment request.

[0028] Specifically, taking a PTC heater as an example, the system sets the target PTC temperature, or the target outlet water temperature TempDsr, based on the current heating needs of the passenger compartment or the power battery. Users can set the target water temperature by interacting with the vehicle's infotainment system, which can be done via voice, touchscreen, or mechanical buttons. For example, a user can input "Please set the air conditioning temperature to 23℃," and the system will recognize the user's voice, generate a corresponding air conditioning adjustment request, and send it to the control unit. The control unit then extracts the target water temperature (e.g., 23℃) from the air conditioning adjustment request. Subsequently, a temperature sensor located on the PTC heater's outlet water pipe collects the actual PTC outlet water temperature, TempAct, in real time. The controller calculates the current temperature deviation, TempErr, in real time, based on the target temperature minus the actual temperature.

[0029] Based on the calculation logic of temperature deviation, the expression for the current temperature deviation TempErr is as follows: TempErr=TempDsr-TempAct formula (1) Where TempErr is the current temperature deviation, TempDsr is the target PTC outlet water temperature, and TempAct is the actual PTC outlet water temperature. This temperature deviation, TempErr, not only reflects the distance between the current temperature and the target, but its positive or negative sign is also the benchmark for subsequent judgment of whether the demand is for heating or heat dissipation.

[0030] Step S110 involves monitoring the actual temperature change trend to identify either a near-heating or near-cooling condition. The near-heating condition indicates that the heater temperature is below the target temperature but gradually approaches it; the near-cooling condition indicates that the heater temperature is above the target temperature but gradually approaches it. Due to the nonlinear asymmetric characteristics of the water temperature system, decoupling the heating and cooling control helps improve control accuracy. The control unit can continuously monitor the historical trajectory of the actual PTC outlet water temperature (TempAct) through internal state machine logic. When the system identifies a specific condition of "near-heating" or "near-cooling," a subsequent predictive compensation mechanism is triggered. This condition identification mechanism reduces unnecessary control interference when the temperature is far from the target or fluctuating irregularly, thus improving the stability of the control logic.

[0031] Step S120: Calculate the current temperature change rate of the actual temperature; determine the target proportional term negative gain base coefficient under the current temperature deviation and the current temperature change rate based on the first mapping relationship; wherein the first mapping relationship is used to characterize the proportional term negative gain base coefficient corresponding to different temperature deviations and temperature change rates, and the proportional term negative gain base coefficient corresponding to the heating close working condition and the cooling close working condition are different.

[0032] In some exemplary embodiments, the rate of temperature change is a physical quantity characterizing the intensity of thermal inertia release in the system. A faster rate generally indicates greater kinetic energy and latent heat within the system, and a higher probability of exceeding the target temperature. Therefore, it is necessary to calculate the current rate of temperature change based on the actual temperature as the basis for subsequent predictive control.

[0033] In some embodiments, a first two-dimensional table can be pre-constructed in the storage unit of the control terminal to store a first mapping relationship. Specifically, the horizontal axis of the first two-dimensional table is the temperature deviation TempErr, and the vertical axis is the temperature change rate. The temperature deviation TempErr and the temperature change rate calculated in real time are used as indices to input into the two-dimensional table. Through table lookup and interpolation algorithms, the corresponding target proportional term negative gain base coefficient is output. Through the two-dimensional table mapping, nonlinear dynamic adjustment is achieved, where the absolute value of the output negative gain base coefficient is larger as the temperature approaches the target and the rate of change is faster. This provides a quantified damping force to address overshoot defects caused by thermal inertia. Under the temperature rise approach condition, the sign of the temperature deviation TempErr is positive, while under the temperature fall approach condition, the sign of the temperature deviation TempErr is negative. The deviation values ​​and temperature change rates under the two conditions can correspond to two different sets of proportional term negative gain base coefficients in the two-dimensional table, thereby achieving adaptive adjustment under different conditions.

[0034] Step S130: Determine the target proportional coefficient based on the negative gain base coefficient of the target proportional term; and correct the output power of the heater based on the target proportional coefficient.

[0035] In some embodiments, a target proportional gain Kp can be applied to the incremental PI (Proportional-Integral) control algorithm. By setting the target proportional gain Kp to a value with a reverse control effect, the proportional term generates an adjustment amount that is opposite to the conventional logic in the incremental calculation, thereby reducing or increasing the output power of the PTC heater in advance. This prediction-based power correction utilizes its own thermal inertia to complete the temperature change in the final stage, reducing excess heat and helping the water temperature to smoothly approach the target temperature.

[0036] This application calculates the current rate of temperature change in real time and determines the target proportional term negative gain base coefficient based on the temperature deviation and the rate of temperature change, thereby introducing predictive reverse damping or compensation into incremental proportional-integral control. This scheme overcomes the limitations of traditional control algorithms that rely solely on passive adjustment based on the current deviation. It can detect the changing trend in advance and reduce or increase the output power when the temperature rapidly approaches the target value. This predictive adjustment cleverly utilizes the system's own thermal inertia, effectively reducing the probability of the actual water temperature exceeding the target temperature, greatly improving the problems of temperature overshoot, overshoot, and repeated oscillations, and enhancing the stability of temperature control.

[0037] In some embodiments, this application provides a smoother and more interference-resistant calculation method for the step of calculating the current temperature change rate of the actual temperature. Specifically, the step of calculating the current temperature change rate of the actual temperature includes: recording the trigger times of N consecutive monotonic temperature changes to form a time queue, where N is a positive integer greater than or equal to 3; and determining the real-time temperature change rate based on the time queue and the total time. In vehicle electromagnetic and fluid dynamic environments, temperature sensors arranged on the outlet pipe of the PTC heater are easily affected by high-frequency electromagnetic interference and local turbulence of the coolant, resulting in fluctuating temperature signals. If the change rate is calculated solely based on the temperature difference between two adjacent sampling points, small signal noise will be amplified by the differential operation, generating rate noise. This sudden rate change input into the predictive control algorithm will cause the target proportional coefficient Kp to jump, thereby causing oscillations in the PTC heating power.

[0038] In some exemplary embodiments, taking N equal to 3 as an example, the steps of calculating the current temperature change rate of the actual temperature include: recording the trigger times of three consecutive monotonic temperature changes to form a time queue; and determining the real-time temperature change rate based on the time queue and the total time.

[0039] To mitigate the aforementioned rate noise issue, a state machine can be maintained at the control terminal to capture valid temperature change edges. When the actual PTC outlet water temperature (TempAct) undergoes a clear change (e.g., an increase or decrease of 1°C), the state machine records the trigger time of this event. A temperature change threshold can be set; if the continuous change in the actual outlet water temperature reaches this threshold, power compensation or adjustment is considered appropriate, i.e., the trigger condition for output power control is met. To filter out occasional fluctuations, four consecutive moments can be recorded, denoted as t1, t2, t3, and t4, where t1 is the initial reference moment, and t2, t3, and t4 are the trigger times for the subsequent three temperature change edges. t4 corresponds to the moment when the temperature change value reaches the temperature change threshold, while t2 and t3 are sampling moments determined based on a pre-configured sampling step size within the time sampling window. These four moments form a time queue. The controller calculates the total time consumed by the cumulative 3°C change based on the time queue and determines the real-time temperature change rate accordingly. By recording the trigger times of three consecutive monotonic temperature changes, a low-pass filter was applied in the time domain to smooth the rate curve, so that the calculated real-time temperature change rate can more realistically reflect the macroscopic thermodynamic inertial trend of the water temperature system.

[0040] In some exemplary embodiments, the step of determining the real-time temperature change rate based on the time queue and the total time includes: using the trigger times of multiple adjacent temperature change edges with the same trend as flag bits based on the time queue, calculating the time interval between corresponding flag bits; and calculating the real-time temperature change rate using multiple consecutive time intervals as the total time. Due to fluctuations in pump speed or the passage of air bubbles in the pipeline, the actual PTC outlet water temperature TempAct may experience a brief drop in an overall upward trend. If all temperature change moments are included in the calculation, the reverse fluctuations will interfere with the accuracy of the time interval. Therefore, based on the time queue, multiple temperature change edge trigger times with the same trend (i.e., both rising edges or both falling edges) are used as flag bits. The following uses three temperature change edge trigger times as an example to illustrate this embodiment. Under the heating condition, the state machine only captures the moment when the temperature rises. Assume that the three consecutive rising edge flag bits captured are ta, tb, and tc. The time interval between the corresponding flag bits is calculated, i.e., the first interval is tb minus ta, and the second interval is tc minus tb. These two time intervals represent the physical time required for the temperature to rise to a specific value. Subsequently, the real-time temperature change rate is calculated using the sum of two consecutive time intervals as the total time. By filtering out interference from anisotropic fluctuations, it is ensured that the time intervals involved in the calculation reflect the thermodynamic work done in a single direction, thus improving the fidelity of the real-time temperature change rate.

[0041] In some exemplary embodiments, in order to improve the problem of rate update lag caused by fixed window calculation, after determining the real-time temperature change rate based on the time queue and the total time, the method further includes: when a new temperature change is detected at the trigger time, updating the time queue so that only the most recent N trigger times are always retained in the time queue; updating the real-time temperature change rate based on the updated time queue, and using the average of the real-time temperature change rates obtained by the preset number of updates as the final real-time temperature change rate.

[0042] Using a fixed window size for rate calculation results in a stepped lag in rate updates. As the water temperature approaches the target temperature, this lag prevents the controller from promptly detecting rate decays or surges. When the state machine detects a new temperature change along its trigger time, it updates the time queue using a first-in, first-out (FIFO) principle, discarding the oldest trigger time and pushing the new trigger time into the queue. Then, based on the updated time queue, a new real-time temperature change rate is recalculated. To suppress minor fluctuations from single updates, a rate buffer pool containing a preset number of updates (e.g., the last 5 updates) is maintained. The arithmetic mean of all real-time temperature change rates in this buffer pool is calculated and used as the final real-time temperature change rate. This moving window mechanism transforms rate calculation into a continuously sliding, smooth curve, balancing the algorithm's real-time responsiveness to temperature trend changes with its smoothness against interference.

[0043] Specifically, taking a time queue containing three trigger moments as an example, the steps of using state machine movement to calculate the real-time temperature change rate of the actual temperature TempAct include: recording the trigger moments of three consecutive monotonic temperature changes, denoted as t1, t2, t3 and t4 respectively; and calculating the total time consumed for the cumulative change of the preset temperature value (e.g., a continuous change of 3℃) as (t4-t1).

[0044] When a new temperature change is detected at the trigger time tnew, the time queue is updated by assigning the value of t2 to t1, the value of t3 to t2, the value of t4 to t3, and the value of tnew to t4, so as to achieve real-time smooth update of the real-time temperature change rate.

[0045] In actual vehicle operating environments, high-pressure on-board temperature sensors are susceptible to high-voltage electromagnetic interference and coolant turbulence, resulting in high-frequency random noise mixed in with the acquired PTC actual outlet water temperature (TempAct) signal. If the temperature change rate is obtained by directly calculating the differential temperature of adjacent sampling points, the noise will be greatly amplified, causing drastic jumps in the calculated rate. This leads to high-frequency oscillations in the controller's output power, severely affecting the PTC heater's lifespan and temperature control stability. To overcome this deficiency, this embodiment employs a moving window state machine algorithm to accurately and smoothly calculate the real-time temperature change rate. Specifically, the state machine records the trigger time when it detects a monotonic change (rising or falling edge) of a preset amount (e.g., 1°C) in the PTC actual outlet water temperature (TempAct). The vehicle thermal management controller records the trigger times of three consecutive monotonic temperature changes, denoted as t1, t2, t3, and t4. At this point, the temperature has cumulatively changed by 3°C, and the total time consumed is (t4-t1). When a new temperature change edge is detected at the trigger time tnew, the state machine initiates a queue movement mechanism: rolling the historical data in the time queue forward, i.e., performing an assignment operation, assigning the value of t2 to t1, the value of t3 to t2, the value of t4 to t3, and the value of tnew to t4. Through this rolling update of the time queue, the real-time temperature change rate can be updated smoothly and in real-time based on the latest temperature change edge within each control cycle. In contrast, if the traditional fixed-time-step differential method is used, the rate calculation will be inaccurate due to insufficient resolution when the temperature change is slow, and the rate will be extremely high due to noise when the temperature changes abruptly. This embodiment measures the time difference by fixing the temperature change amount (e.g., 3℃) and uses a moving window state machine for rolling filtering, which is equivalent to implementing an adaptive low-pass filter in the time domain. This completely filters out the high-frequency noise from the temperature sensor and ensures a fast and smooth response to the real temperature change trend, providing a highly robust rate input for subsequent reverse gain control.

[0046] In some embodiments, the step of monitoring the actual temperature change trend to identify the heating approach condition or the cooling approach condition includes: if the temperature changes M times consecutively show an increasing trend and the actual temperature is less than the target temperature, then the current operating condition is determined to be the heating approach condition, where M is a positive integer greater than or equal to 3; if the temperature changes M times consecutively show a decreasing trend and the actual temperature is greater than the target temperature, then the current operating condition is determined to be the cooling approach condition.

[0047] During the heating phase, the PTC heater actively injects heat, resulting in rapid heating and high thermal inertia. During the cooling phase, heat is dissipated through natural heat dissipation from the pipes or passive heat exchange from the cabin heating core, leading to a relatively slow cooling process. First, a state machine monitors the microscopic changes in actual temperature, confirming an increasing trend for M consecutive temperature changes. This constitutes the condition for determining that the system is in a macroscopic heating state. Based on this, a judgment is made in conjunction with the macroscopic temperature deviation: only when the actual temperature is less than the target temperature (i.e., temperature deviation TempErr is greater than 0) does it indicate that the system is rising towards the target temperature, and the current operating condition is determined to be the near-heating condition. Similarly, if the M consecutive temperature changes show a decreasing trend, and the actual temperature is greater than the target temperature (i.e., temperature deviation TempErr is less than 0), it indicates that the system is falling back from a high temperature, and the cooling condition is determined to be the near-cooling condition. This dynamic and static combined identification mechanism decouples the heating and cooling processes of the nonlinear asymmetric system, avoiding misjudgments that may result from solely relying on the sign of the temperature difference. The specific value of M can be determined according to actual application requirements; for example, M can be set to 3.

[0048] In some exemplary embodiments, to adapt to complex vehicle boundary conditions, the step of determining the target proportional coefficient based on the target proportional term negative gain base coefficient includes: determining a first correction value for the target temperature and the current air conditioning blower fan speed setting based on a second mapping relationship; wherein the second mapping relationship is used to characterize the proportional coefficient under different target temperatures and air conditioning blower fan speed settings; determining a second correction value for the deviation between the ambient temperature and the current temperature based on a third mapping relationship; wherein the third mapping relationship is used to characterize the proportional coefficient under different ambient temperatures and temperature deviations; and using the product of the first correction value, the second correction value, and the target proportional term negative gain base coefficient as the target proportional coefficient.

[0049] The airflow setting of the air conditioner blower affects the heat dissipation rate of the heater core. A larger airflow removes more heat, making the water temperature system less sensitive to reductions in PTC heating power, requiring a smaller negative gain damping. Conversely, a smaller airflow leads to heat accumulation, requiring a larger negative gain damping. The ambient temperature affects the natural heat dissipation rate of the piping. At lower ambient temperatures, the system dissipates heat quickly naturally, requiring a smaller negative gain damping; at higher ambient temperatures, natural heat dissipation is slower, requiring a larger negative gain damping. Inputting the target temperature and the air conditioner blower airflow setting into a preset second two-dimensional table outputs a first correction value. Inputting the ambient temperature and the current temperature deviation (TempErr) into a preset third two-dimensional table (third mapping relationship) outputs a second correction value. The second two-dimensional table records the second mapping relationship, and the third two-dimensional table records the third mapping relationship. The horizontal axis of the second two-dimensional table can be the air conditioner blower airflow setting, and the vertical axis can be the target temperature. By querying the second two-dimensional table using the air conditioner blower airflow setting and the target temperature as input, the corresponding first correction value can be obtained. The second mapping relationship can be configured based on experimental data; the specific configuration process is not limited here. The horizontal axis of the third two-dimensional table can be the external ambient temperature, and the vertical axis can be the temperature deviation. By querying the third two-dimensional table using the external ambient temperature and temperature deviation as input, the corresponding second correction value can be obtained. The third mapping relationship can be configured based on experimental data; the specific configuration process is not limited here.

[0050] In the vehicle thermal management system, the heat load of the PTC heater depends not only on the internal circulation of the water circuit but also on the strong coupling effect of the vehicle's multi-dimensional boundary conditions. For example, when the air conditioning blower fan speed is at its maximum, the airflow through the heater core is extremely high, and the heat carried away increases exponentially. At this time, the equivalent thermal time constant of the water circuit system decreases, and the system's sensitivity to PTC power changes is reduced. Furthermore, the natural heat dissipation rate of the pipeline to the external environment varies greatly under different external ambient temperatures. Simultaneously, different target PTC outlet water temperatures (TempDsr) correspond to different PTC material resistance characteristics. If only a fixed proportional negative gain base coefficient is used, the algorithm will result in extremely slow heating under high airflow conditions in winter due to excessive damping, while under low airflow conditions in spring and autumn due to insufficient damping, leading to temperature control instability. To eliminate the interference of vehicle boundary conditions on temperature control accuracy, this embodiment introduces a multi-dimensional adaptive correction mechanism. Specifically, the current target PTC outlet water temperature (TempDsr) and the air conditioning blower fan speed setting are used as inputs. A preset second two-dimensional table is consulted to output a first correction value (f1). This first correction value (f1) dynamically adjusts the gain of the target proportional coefficient based on the strength of heat removal by the airflow, eliminating the impact of airflow fluctuations on water temperature control. Simultaneously, the vehicle thermal management controller uses the collected current external ambient temperature and the current temperature deviation (TempErr) as inputs, consults a preset third two-dimensional table, and outputs a second correction value (f2). This second correction value (f2) performs secondary energy compensation on the target proportional coefficient based on the difference in the natural heat dissipation rate of the pipeline caused by the ambient temperature difference. Finally, the negative gain base coefficient of the proportional term is multiplied by the first correction value (f1) and the second correction value (f2) to calculate the final target proportional coefficient. Through this multi-dimensional adaptive correction, the control algorithm can automatically identify and adapt to different seasons, different fan speed settings, and different target temperatures, greatly improving the control accuracy and robustness of the algorithm under complex vehicle operating conditions.

[0051] In some exemplary embodiments, based on the multi-dimensional correction logic, the calculation formula for the target scaling factor Kp is as follows: Kp = Kp_base × f1 × f2 (Equation 2) Wherein, Kp is the target proportional coefficient, Kp_base is the base coefficient of the negative gain of the target proportional term, f1 is the first correction value, and f2 is the second correction value. By converting air volume load and ambient heat dissipation into correction coefficients and multiplying them with the base negative gain coefficient, the final target proportional coefficient Kp has environmental adaptability, improving control accuracy and robustness.

[0052] In some exemplary embodiments, the step of correcting the output power of the heater based on the target proportionality coefficient includes: setting the target proportionality coefficient to a negative number when the temperature rises to near the operating condition, so as to reduce the output power of the heater in advance; and setting the target proportionality coefficient to a positive number when the temperature drops to near the operating condition, so as to increase the output power of the PTC heater in advance.

[0053] This application uses an incremental PI algorithm, and the formula for calculating the power increment is as follows: Equation (3) Where u(k) is the output power (i.e. the final control power), Kp is the target proportional coefficient, Ki is the integral coefficient, e(i) is the temperature deviation TempErr in the i-th control cycle, and k is the control cycle.

[0054] When approaching the target temperature during the temperature rise phase, the actual temperature has not yet reached the target temperature, and the temperature deviation TempErr is greater than 0. The controller sets the target proportional coefficient Kp to a negative number. At this time, the proportional term has a negative regulatory effect in the incremental calculation. When the water temperature rapidly approaches the target value, the algorithm predictively reduces the output power of the PTC heater, utilizing the accumulated thermal inertia in the pipeline and medium to allow the water temperature to smoothly transition to the target temperature. When approaching the target temperature during the temperature drop phase, the actual temperature is higher than the target temperature, and the temperature deviation TempErr is less than 0. The controller sets the target proportional coefficient Kp to a positive number. The positive Kp, combined with the negative temperature difference change, plays a predictive regulatory role in the incremental calculation, increasing the PTC heating power in advance to create thermal support before the water temperature falls below the target, thus slowing down the temperature decline. This symbolic configuration logic gives the incremental PI algorithm the ability to proactively reverse damping.

[0055] The automotive coolant temperature control system is a typical nonlinear, asymmetric physical system. The PTC heater, as an active heat source, responds rapidly and has controllable power during heating; however, the cooling process relies entirely on natural heat dissipation from the pipes or convective heat transfer from the cold air in the air conditioning unit, constituting a passive cooling process. Its response speed and thermal inertia differ by orders of magnitude from the heating process. Using the same set of PID control parameters to simultaneously handle both heating and cooling processes can lead to the awkward situation of "adjusting the heating parameters well, but experiencing temperature control misalignment during cooling; adapting to the cooling parameters, but experiencing severe overshoot during heating." To address this tuning constraint, this embodiment uses a state machine to finely monitor and identify the changing trend of the actual PTC outlet temperature, TempAct. Specifically, the state machine continuously records the direction of temperature change edges. If three consecutive temperature change edges show an increasing trend (i.e., the temperature continues to rise), and the current actual PTC outlet water temperature TempAct is still lower than the PTC target outlet water temperature TempDsr (i.e., the temperature deviation TempErr is greater than 0), then the current operating condition is determined to be a near-heating condition, which will soon face the risk of overshoot due to the accumulation of active heating. Conversely, if three consecutive temperature change edges show a decreasing trend (i.e., the temperature continues to fall), and the current actual PTC outlet water temperature TempAct is already higher than the PTC target outlet water temperature TempDsr (i.e., the temperature deviation TempErr is less than 0), then the current operating condition is determined to be a near-cooling condition, which will soon face the risk of excessive temperature drop due to passive heat dissipation. Based on this, the preset first mapping relationship is designed as a first two-dimensional table, where the horizontal axis is the temperature deviation TempErr (including positive and negative values), and the vertical axis is the real-time temperature change rate. The first two-dimensional table uses the positive and negative signs of the temperature deviation TempErr as a natural dividing line, dividing the table into a positive temperature difference zone (corresponding to the heating process) and a negative temperature difference zone (corresponding to the cooling process), respectively, and fills in control coefficients independently calibrated for the heating and cooling conditions. When the system is in the near-heating condition, the vehicle thermal management controller looks up the corresponding heating negative gain base coefficient from the table; when the system is in the near-cooling condition, it looks up the corresponding cooling negative gain base coefficient from the table. These heating and cooling negative gain base coefficients correspond to the aforementioned target proportional term negative gain base coefficient. Through this condition identification and dual-zone lookup mechanism, complete decoupling of the heating and cooling control logic is achieved, perfectly solving the temperature control problem of nonlinear asymmetric systems and ensuring that the system achieves optimal damping and compensation effects during both heating and cooling phases.

[0056] This application accurately identifies near-heating and near-cooling operating conditions by continuously monitoring the actual temperature change trend and combining the positive and negative signs of the temperature deviation. Under the near-heating condition, the target proportional coefficient is set to a negative number, and under the near-cooling condition, it is set to a positive number. This decoupled control logic fully adapts to the physical nature of the water temperature system as a nonlinear asymmetric system, avoiding the dilemma of mutual constraint between heating and cooling parameters in traditional algorithms. This allows the system to maintain excellent control performance in both active heating and passive cooling processes, which are fundamentally different.

[0057] This application uses a state machine to calculate the rate of water temperature change in real time. When the temperature rapidly approaches the target value, it uses inverse gain to predictively reduce or compensate the PTC power in advance. Under the condition of approaching temperature rise, the proportional coefficient is set to a negative value, causing the proportional term to have a negative adjustment effect in the incremental calculation, predictively reducing the output power of the PTC heater and utilizing the system's residual thermal inertia to smoothly transition to the target temperature. Under the condition of approaching temperature drop, the proportional coefficient is set to a positive value, combining the positive proportional coefficient with the negative temperature deviation to have a positive adjustment effect in the incremental calculation, predictively increasing the output power of the PTC heater and preventing the water temperature from continuing to drop. This inverse gain control mechanism fundamentally overcomes the control lag caused by thermal inertia, eliminates temperature overshoot and repeated oscillations, and achieves high-precision, overshoot-free adaptive temperature regulation.

[0058] This application introduces a multi-dimensional adaptive correction mechanism. By acquiring vehicle boundary conditions such as target temperature, air conditioning blower fan speed setting, and ambient temperature, the base coefficient of the negative gain of the target proportional term is double-corrected. This scheme quantifies external disturbance sources such as airflow load and environmental heat dissipation as correction coefficients, giving the final target proportional coefficient a strong environmental adaptability. This effectively overcomes the deficiency of insufficient control accuracy of a single control parameter under different seasons and airflow conditions, and significantly improves the robustness of the heater power control system under complex boundary conditions.

[0059] In some embodiments, in order to balance extreme heating speed and temperature control accuracy, the method further includes: when the temperature deviation TempErr is greater than or equal to a first threshold, determining the target output power applied to the PTC heater through a first control method, wherein the first control method is an open-loop control used to rapidly heat up the PTC heater; and when the temperature deviation TempErr is less than a second threshold, determining the output power applied to the PTC heater through a second control method, wherein the second control method is a closed-loop control, and the second control method is the aforementioned heater power control method.

[0060] When starting a cold engine in extremely cold weather, the initial temperature deviation (TempErr) between the actual PTC coolant temperature and the target coolant temperature is relatively large. If relying entirely on the closed-loop control algorithm, the integral term requires time to accumulate errors, resulting in a relatively slow increase in the output power of the PTC heater during the initial startup phase. When the detected temperature deviation (TempErr) is greater than or equal to a first threshold (e.g., 30°C), open-loop control is switched to. In open-loop control mode, the PTC heater is controlled to heat at a higher power level, reducing the temperature difference in a shorter time. When the temperature deviation (TempErr) decreases and falls below a second threshold (e.g., 10°C), closed-loop control is switched to apply reverse damping using a predictive negative gain mechanism, allowing the coolant temperature to smoothly stabilize at the target temperature.

[0061] In some exemplary embodiments, determining the output power acting on the PTC heater using a first control method includes: determining the heating rate of the PTC heater; calculating the product between the temperature deviation TempErr and a preset heating coefficient to obtain a base output power; determining an automatic adjustment power; reducing the automatic adjustment power when the heating rate is lower than a first time threshold; maintaining the automatic adjustment power unchanged when the heating rate is higher than or equal to the first time threshold and lower than a second time threshold; increasing the automatic adjustment power when the heating rate is higher than or equal to the second time threshold; and using the sum of the base output power and the automatic adjustment power as the output power.

[0062] In extremely cold environments, the antifreeze has a higher viscosity, increasing the water pump's circulation resistance. If a fixed maximum power is output during the open-loop phase, but the antifreeze flow is impeded, the local temperature of the PTC heating core may be excessively high. The base output power is calculated by multiplying the initial temperature deviation (TempErr) by a preset heating coefficient. Simultaneously, the actual heating rate of the PTC heater is monitored in real time. If the heating rate is too fast (time below the first time threshold), it indicates that heat is not being effectively dissipated, and the automatic adjustment power is reduced. If the heating rate is within the normal range (between the first and second time thresholds), the automatic adjustment power remains unchanged. If the heating rate is too slow (time above the second time threshold), it indicates that the ambient temperature is low and heat is dissipating rapidly, and the automatic adjustment power is increased. Finally, the base output power is added to the dynamically adjusted automatic adjustment power to obtain the final output power for the open-loop phase, achieving safe dynamic protection during the open-loop phase.

[0063] In some exemplary embodiments, in order to address steady-state heat loss in frigid environments, the method further includes: acquiring the actual temperature inside the vehicle and the ambient temperature outside the vehicle; searching for a reference duty cycle signal corresponding to the actual temperature inside the vehicle and the ambient temperature outside the vehicle in a pre-established two-dimensional table; and adding the duty cycle signal calculated by the aforementioned heater power control method to the reference duty cycle signal to obtain the final PTC duty cycle signal for controlling the operation of the PTC heater.

[0064] In harsh winters, heat inside the vehicle is lost to the outside environment through the vehicle body. During the steady-state heat preservation phase, the water temperature deviation (TempErr) is small, and the maintenance power calculated by the closed-loop PI algorithm may be insufficient to offset the heat loss to the outside, causing the interior temperature to drop slowly. The system uses temperature sensors to acquire the actual interior temperature and the outside ambient temperature in real time. A calibrated two-dimensional table is pre-stored, with the interior temperature and the outside ambient temperature on the horizontal and vertical axes, respectively. The table stores the reference duty cycle signal (i.e., feedforward compensation power) required to maintain thermal balance inside the vehicle under a specific temperature difference between the inside and outside. The larger the temperature difference between the inside and outside, the larger the reference duty cycle signal obtained from the table. The dynamic duty cycle signal calculated by the incremental PI algorithm is added to the feedforward reference duty cycle signal obtained from the table to obtain the total duty cycle signal for controlling the PTC heater. By introducing feedforward compensation, heat loss is predicted in advance and power is supplemented, which helps maintain the dynamic thermal balance inside the vehicle.

[0065] Please see Figure 2 Based on the same concept, this application also provides a heater power control system, which includes: a temperature detection module 20, an operating condition identification module 21, a basic coefficient determination module 22, and a correction control module 23.

[0066] The temperature detection module 20 is used to acquire the actual temperature of the heater and calculate the current temperature deviation based on the target temperature and the actual temperature; wherein, the target temperature is determined according to the input air conditioning adjustment request. The hardware entity of the temperature detection module 20 typically includes a temperature sensor arranged at the outlet of the PTC heater and related signal conditioning circuitry. This module is responsible for acquiring the actual temperature of the heater, TempAct, in real time, receiving the target temperature, TempDsr, and calculating the current temperature deviation, TempErr.

[0067] The operating condition identification module 21 monitors the actual temperature change trend to identify either a heating-approaching or cooling-approaching operating condition. The heating-approaching condition indicates that the heater temperature is below the target temperature and gradually approaches it; the cooling-approaching condition indicates that the heater temperature is above the target temperature and gradually approaches it. The operating condition identification module 21 uses built-in state machine logic to track temperature changes and, combined with the sign of the temperature deviation, identifies whether the current system is in a heating-approaching or cooling-approaching condition, thus achieving logical isolation between the heating and cooling processes.

[0068] The basic coefficient determination module 22 is used to calculate the current rate of temperature change of the actual temperature; based on the first mapping relationship, it determines the target proportional term negative gain basic coefficient under the current temperature deviation and the current rate of temperature change; wherein the first mapping relationship is used to characterize the proportional term negative gain basic coefficient corresponding to different temperature deviations and rates of temperature change, and the proportional term negative gain basic coefficient corresponding to the near-heating condition and the near-cooling condition are different. The basic coefficient determination module uses a moving window algorithm to calculate the current rate of temperature change of the actual temperature. Subsequently, it calls the first mapping relationship stored in non-volatile memory, uses the current temperature deviation TempErr and the rate of temperature change as a joint index, looks up the table and interpolates to calculate the target proportional term negative gain basic coefficient. The temperature deviation TempErr is used to distinguish between temperature rise and fall, implementing two sets of coefficients for the two processes.

[0069] The correction control module 23 is used to determine the target proportional coefficient based on the base coefficient of the negative gain of the target proportional term, and to correct the output power of the heater based on the target proportional coefficient. The correction control module performs multi-dimensional corrections based on the base coefficient of the negative gain of the target proportional term, combined with external variables such as ambient temperature and blower airflow, to determine the final target proportional coefficient Kp. Subsequently, Kp is substituted into the incremental PI algorithm engine to calculate the final power increment command, driving the power module inside the PTC heater to correct the heater's output power. This system, through its modular architecture, improves the integration and computational efficiency of the vehicle's thermal management system.

[0070] The specific interaction process between the modules has been described in detail in the aforementioned method embodiments, and will not be repeated here.

[0071] This application also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the heater power control method as described in any of the foregoing embodiments. This computer-readable storage medium can be a non-volatile memory, such as electrically erasable programmable read-only memory or flash memory, pre-installed within the thermal management controller before the vehicle leaves the factory; it can also be a software upgrade package image file on a cloud server, wirelessly downloaded to the vehicle terminal via a cellular network and written into the controller's storage area. By embedding the algorithm in the form of a software medium, the portability of the algorithm across different vehicle platforms is improved, and functional updates via remote upgrade technology are facilitated. Specifically, the computer-readable storage medium can be a tangible non-volatile memory, such as flash memory, read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), or solid-state disk (SSD). The computer program contains instruction steps executable by the microprocessor of the vehicle's thermal management controller. When the vehicle's thermal management controller is powered on, the microprocessor reads the computer program from this storage medium and loads it into the running memory for execution. During program execution, the control microprocessor reads sensor data, runs a state machine to monitor temperature trends, calculates the real-time temperature change rate, looks up a table to determine the proportional coefficient, and applies it to the incremental PI regulator, thereby outputting precise power control commands. This computer-readable storage medium embeds advanced predictive temperature control algorithms into a software product, greatly improving the portability and compatibility of the control algorithm across different vehicle controller platforms. It also facilitates remote upgrades and iterative optimizations of the algorithm via over-the-air (OTA) updates, aligning with the development trend of software-defined vehicles.

[0072] This application also provides a vehicle including a heater power control system as described in the foregoing embodiments. This heater power control system, as the core hub of the thermal management domain, interacts with the vehicle's intelligent cockpit domain, power battery management system, and vehicle controller. During the heating process, the system calculates the rate of temperature change in real time. Just as the water temperature is about to reach the target, it applies a reverse negative gain damping correction based on multi-dimensional boundary conditions to flexibly reduce the output power of the PTC in advance, allowing the water temperature to smoothly approach the target temperature line. This improves the heating comfort of the passenger compartment, reduces the ineffective energy consumption of the thermal management system, and helps to improve the real-world driving range of new energy vehicles in winter.

[0073] Specifically, the vehicle is a new energy electric vehicle. In new energy electric vehicles, vehicle energy management and thermal management are the core factors determining driving range. To achieve coordinated energy control at the vehicle level, the vehicle thermal management controller and the vehicle controller (VCU) communicate at high speed through the vehicle's internal Controller Area Network (CAN) bus. Through the CAN bus, the vehicle thermal management controller can obtain vehicle boundary condition parameters sent by the vehicle controller in milliseconds, including but not limited to: the vehicle's current speed, the current state of charge of the power battery, the current actual airflow setting of the air conditioning blower, and the real-time ambient temperature collected by the external temperature sensor. Simultaneously, the vehicle thermal management controller can also transmit information such as the actual PTC outlet temperature, current operating status, and actual power consumption back to the vehicle controller in real time. This high-speed information exchange based on the CAN bus allows the thermal management algorithm to perfectly integrate the vehicle's operating status, automatically prioritizing energy consumption control when battery power is low and automatically adjusting the airflow correction coefficient during high-speed driving. This achieves closed-loop, coordinated, and intelligent scheduling of vehicle energy, ensuring efficient and safe vehicle operation.

[0074] The present application will be further described below through specific embodiments.

[0075] This embodiment aims to verify the effectiveness of a predictive incremental PI control method based on the rate of temperature change in suppressing PTC water temperature overshoot. Test conditions: ambient temperature -10℃, target outlet water temperature set to 60℃, initial water temperature 10℃. Air conditioning blower airflow set to medium. Operating steps: S1: Using the heater power control method of this application, the controller collects the actual outlet water temperature of the PTC in real time and calculates the temperature deviation.

[0076] S2: The state machine monitors temperature changes and identifies when the temperature rise is close to the operating condition.

[0077] S3: The moving window algorithm is used to calculate the rate of temperature change.

[0078] S4: Based on the temperature deviation and the rate of temperature change, look up the table to obtain the base coefficient of the negative gain of the target proportional term, and then make corrections based on the ambient temperature and airflow level to obtain the target proportional coefficient Kp (which is negative under near-temperature conditions).

[0079] S5: Substitute the target proportional coefficient Kp into the incremental PI algorithm and output control commands to adjust the PTC heating power.

[0080] This comparative example uses the traditional PID control method, and other test conditions are the same as those in the above embodiment. Operating steps: The controller collects the actual outlet water temperature of the PTC in real time and calculates the temperature deviation; it uses fixed proportional coefficients (positive numbers), integral coefficients and derivative coefficients, substitutes them into the positional PID algorithm, and outputs control commands to adjust the PTC heating power.

[0081] The control method employed in this application generates predictive reverse damping by introducing a negative target proportional coefficient when the water temperature approaches the target temperature, effectively reducing heating power. Compared to traditional PID control methods, it significantly improves temperature overshoot and oscillation issues and shortens the thermal equilibrium time for the system to reach a steady state. This demonstrates that the technical solution of this application has a good technical effect in overcoming temperature control defects caused by thermal inertia.

[0082] In one exemplary embodiment, a controller is provided, the internal structure of which can be shown in the following diagram. Figure 3 As shown, the controller includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores various data involved in the vehicle range display update method. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a vehicle range display update method.

[0083] Those skilled in the art will understand that Figure 3 The structure shown is a block diagram of a partial structure related to the solution of this application, and does not constitute a limitation on the controller applied thereto by the solution of this application. The specific controller may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0084] In one exemplary embodiment, a controller is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0085] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0086] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A heater power control method, characterized in that, include: The actual temperature of the heater is obtained, and the current temperature deviation is calculated based on the target temperature and the actual temperature; wherein the target temperature is determined based on the input air conditioning adjustment request; The actual temperature change trend is monitored to identify the heating approach condition or the cooling approach condition. The heating approach condition is used to characterize that the heater temperature is lower than the target temperature and gradually approaches the target temperature; the cooling approach condition is used to characterize that the heater temperature is higher than the target temperature and gradually approaches the target temperature. Calculate the current temperature change rate of the actual temperature; determine the target proportional term negative gain base coefficient under the current temperature deviation and the current temperature change rate based on the first mapping relationship; wherein, the first mapping relationship is used to characterize the proportional term negative gain base coefficient corresponding to different temperature deviations and temperature change rates, and the proportional term negative gain base coefficient corresponding to the heating approach condition and the cooling approach condition are different. The target proportional coefficient is determined based on the negative gain base coefficient of the target proportional term; and the output power of the heater is corrected based on the target proportional coefficient.

2. The heater power control method according to claim 1, characterized in that, The steps for calculating the current rate of temperature change of the actual temperature include: Record the trigger times of N consecutive monotonic temperature changes and form a time queue, where N is a positive integer greater than or equal to 3; The real-time temperature change rate is determined based on the time queue and total time.

3. The heater power control method according to claim 2, characterized in that, The step of determining the real-time temperature change rate based on the time queue and the total time includes: Based on the time queue, the time interval between the corresponding flag bits is calculated using multiple adjacent temperature changes with the same trend along the trigger time as flag bits. The real-time temperature change rate is calculated using multiple consecutive time intervals as the total time.

4. The heater power control method according to claim 2, characterized in that, After determining the real-time temperature change rate based on the time queue and total time, the method further includes: When a new temperature change is detected along the trigger time, the time queue is updated so that the time queue always retains the most recent N trigger times; The real-time temperature change rate is updated according to the updated time queue, and the average of the real-time temperature change rates obtained by the preset number of updates is used as the final real-time temperature change rate.

5. The heater power control method according to claim 1, characterized in that, The steps for monitoring the actual temperature change trend to identify whether the temperature is approaching the operating condition or the temperature is approaching the operating condition include: If the temperature changes M times consecutively show an increasing trend, and the actual temperature is less than the target temperature, then the current operating condition is determined to be the temperature rise approaching operating condition, where M is a positive integer greater than or equal to 3. If the temperature changes M times consecutively show a decreasing trend, and the actual temperature is greater than the target temperature, then the current operating condition is determined to be a cooling-approaching operating condition.

6. The heater power control method according to claim 1, characterized in that, The steps for determining the target proportional coefficient based on the base coefficient of the negative gain of the target proportional term include: The target temperature and the first correction value at the current air conditioner blower fan speed setting are determined according to the second mapping relationship; wherein, the second mapping relationship is used to characterize the proportional coefficients of different target temperatures and air conditioner blower fan speed settings; A second correction value is determined based on the deviation between the ambient temperature and the current temperature according to the third mapping relationship; wherein, the third mapping relationship is used to characterize the proportionality coefficient under different ambient temperatures and temperature deviations; The product of the first correction value, the second correction value, and the base coefficient of the negative gain of the target scaling term is taken as the target scaling coefficient.

7. The heater power control method according to claim 1, characterized in that, The step of correcting the heater's output power based on the target proportionality coefficient includes: When the temperature rises to near operating conditions, the target proportional coefficient is set to a negative number to reduce the output power of the heater in advance; When the temperature drops to near operating conditions, the target proportional coefficient is set to a positive number to increase the output power of the PTC heater in advance.

8. A heater power control system, characterized in that, include: A temperature detection module is used to acquire the actual temperature of the heater and calculate the current temperature deviation based on the target temperature and the actual temperature; wherein, the target temperature is determined based on the input air conditioning adjustment request; The operating condition identification module is used to monitor the actual temperature change trend to identify the heating approach condition or the cooling approach condition; wherein, the heating approach condition is used to characterize that the heater temperature is lower than the target temperature and gradually approaches the target temperature; the cooling approach condition is used to characterize that the heater temperature is higher than the target temperature and gradually approaches the target temperature. The base coefficient determination module is used to calculate the current temperature change rate of the actual temperature; and to determine the target proportional term negative gain base coefficient under the current temperature deviation and the current temperature change rate based on the first mapping relationship; wherein, the first mapping relationship is used to characterize the proportional term negative gain base coefficient corresponding to different temperature deviations and temperature change rates, and the proportional term negative gain base coefficient corresponding to the heating close working condition and the cooling close working condition are different. The correction control module is used to determine the target proportional coefficient based on the base coefficient of the negative gain of the target proportional term; and to correct the output power of the heater based on the target proportional coefficient.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the heater power control method as described in any one of claims 1 to 7.

10. A vehicle, characterized in that, Includes the heater power control system as described in claim 8.

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