Intelligent vehicle energy consumption management method and system

Abstract

The invention discloses an intelligent vehicle energy consumption management method and system, and relates to the technical field of intelligent vehicle energy management, and the method comprises the steps: judging whether to start an endurance guarantee mode or not according to the obtained current remaining available energy of a vehicle, the current average energy consumption of the vehicle and the current position of the vehicle; when the endurance guarantee mode is started, a plurality of road sections are divided between the current position of the vehicle and the destination, the total energy consumption budget is calculated according to the current remaining available energy of the vehicle, the maximum energy consumption allowed by each road section and the corresponding recommended vehicle speed are calculated with the condition that the total energy consumption budget is not exceeded as the constraint, and therefore the path with the lowest total energy consumption is formed; and according to the obtained path, controlling the vehicle to run at the recommended vehicle speed under the corresponding road section. The problems that in the prior art, vehicle endurance estimation is not accurate, an effective guarantee scheme is lacked in the low-energy state, and the passive energy-saving effect of a driver is poor are solved, and the mileage anxiety of the last road of a user is relieved.

Description

Technical Field

[0001] This invention relates to the field of intelligent vehicle energy management technology, and in particular to an intelligent vehicle energy consumption management method and system. Background Technology

[0002] When the battery or fuel level is low, drivers cannot accurately determine whether there is enough energy left to reach their destination (such as home, charging station, or gas station). If they break down due to running out of energy, it can easily lead to safety risks.

[0003] In existing technologies, vehicle-mounted range-related functions typically only provide a rough estimate of remaining driving range based on historical average energy consumption data. This fails to adequately consider dynamic factors during driving, such as real-time road conditions, environmental factors, and dynamically adjusted driving routes. Consequently, the estimated range deviates significantly from the actual range, limiting its reference value. Furthermore, when the remaining range is close to or below the distance to the destination, only a low-energy warning is issued. Drivers are forced to passively rely on subjective experience to try reducing speed or turning off the air conditioning to save energy, lacking scientific energy consumption calculation support. This makes it difficult to guarantee energy-saving effects, reduces driving comfort, and negatively impacts the user's driving experience. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes an intelligent vehicle energy consumption management method and system, which solves problems such as inaccurate vehicle range estimation, lack of effective protection solutions in low-energy states, and poor passive energy-saving effects for drivers in the prior art, thereby alleviating users' range anxiety for the "last leg of the journey".

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an intelligent vehicle energy consumption management method, comprising: Based on the vehicle's current remaining available energy, current average energy consumption, and current location, determine whether to activate the range protection mode; When the range protection mode is activated, the vehicle is divided into multiple road segments between its current location and destination. The total energy consumption budget is calculated based on the vehicle's remaining available energy. With the constraint of not exceeding the total energy consumption budget, the maximum energy consumption allowed for each road segment and the corresponding recommended speed are calculated, thus forming the path with the lowest total energy consumption. Based on the obtained path, control the vehicle to drive at the recommended speed on the corresponding road segment.

[0006] As an optional implementation method, the process of determining whether to activate the range protection mode includes: calculating the current range based on the vehicle's current remaining available energy and the vehicle's current average energy consumption; calculating the remaining distance based on the vehicle's current location and destination; setting a critical threshold; and prompting the user whether to activate the range protection mode if the current range is less than the sum of the remaining distance and the critical threshold.

[0007] As an alternative implementation, after obtaining user confirmation to activate the battery life protection mode, the final navigation destination is forcibly locked to the preset destination, and any other original route planning is abandoned.

[0008] As an alternative implementation, the total energy consumption budget is calculated based on the vehicle's current remaining available energy. The total energy consumption budget = the vehicle's current remaining available energy * conversion efficiency - the set safety redundancy.

[0009] As an alternative implementation method, during the process of controlling vehicle driving, the vehicle speed control process includes: taking over the cruise control system or drive torque control, sending target control commands to the cruise control system or vehicle controller via the CAN bus, and controlling the actual vehicle speed below the recommended speed or the maximum speed limit.

[0010] As an alternative implementation method, the energy management process during vehicle operation includes: classifying and managing the power consumption of each electrical appliance, and automatically reducing or shutting down the power of unnecessary high-energy-consuming loads while ensuring safety.

[0011] In a second aspect, the present invention provides an intelligent vehicle energy consumption management system, comprising: The judgment module is configured to determine whether to activate the range protection mode based on the vehicle's current remaining available energy, the vehicle's current average energy consumption, and the vehicle's current location. The planning module is configured to divide the vehicle's current location and destination into multiple road segments when the range protection mode is activated. It calculates the total energy consumption budget based on the vehicle's current remaining available energy, and calculates the maximum energy consumption allowed for each road segment and the corresponding recommended speed, with the constraint of not exceeding the total energy consumption budget, thereby forming the path with the lowest total energy consumption. The control module is configured to control the vehicle's movement at a recommended speed on the corresponding road segment based on the obtained path.

[0012] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0013] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0014] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes an intelligent vehicle energy consumption management method and system. For scenarios where the vehicle's remaining energy is insufficient or just enough to reach a preset destination, it activates a range guarantee mode. Combining core data such as the vehicle's current remaining available energy, real-time average energy consumption, and current location, while also considering variables such as real-time road conditions, environmental factors, and dynamic driving paths, it rationally allocates the total energy consumption budget to each road segment through segmented planning. It calculates the maximum allowable energy consumption and corresponding recommended speed for each road segment, ultimately forming the optimal driving path with the lowest total energy consumption. This ensures a high degree of match between energy consumption estimation and actual driving needs, avoiding energy waste or insufficient energy due to estimation errors. It ensures the vehicle can safely and stably reach its destination, alleviating users' range anxiety for the "last leg of the journey," achieving ultimate homecoming assurance for new energy intelligent vehicles, and enhancing user experience.

[0016] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0018] Figure 1 The flowchart is for the intelligent vehicle energy consumption management method provided in Embodiment 1 of the present invention. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms “comprising” and “including”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0023] As described in the background section, with the rapid development of the intelligent vehicle industry, hybrid and pure electric vehicles have become the mainstream in the market, and their environmental and efficiency advantages are widely recognized. However, the "range anxiety" problem for users remains a core pain point restricting the further popularization of the industry, especially when the vehicle's remaining energy (electricity / fuel) is low. When drivers have insufficient remaining energy, they cannot accurately determine whether the current energy reserves are sufficient to support the vehicle to reach its destination (such as home, charging station, gas station, etc.), which can easily lead to negative emotions such as tension and anxiety. Furthermore, the vehicle may break down due to depleted energy, causing a series of inconveniences and risks, including traffic congestion and road safety hazards.

[0024] In existing technologies, the range-related functions on vehicles are relatively simple, and can only make a rough estimate of the remaining range based on historical average energy consumption data. This estimation method has obvious limitations: it does not fully consider the dynamic influencing factors during driving, including real-time road conditions (such as frequent starts and stops in congested urban areas, constant speed driving on highways, and changes in the gradient of mountain roads), environmental factors (such as the decrease in battery activity due to low temperatures, the increase in energy consumption of the air conditioning system in high or low temperature environments, and the impact of wind speed on driving resistance), and the driver's dynamically adjusted driving path. As a result, the estimated results deviate significantly from the actual range, and have limited reference value.

[0025] More importantly, when the vehicle's remaining range is close to or less than the distance to the destination, the existing system can only issue a simple low-energy warning signal, failing to provide proactive and automated solutions to ensure the vehicle reaches its destination smoothly, thus failing to fundamentally alleviate users' range anxiety. At this point, the driver can only passively rely on their driving experience, attempting to save energy through non-intelligent methods such as reducing speed and turning off the air conditioning. However, this approach lacks scientific energy consumption calculation support, making energy-saving effects difficult to guarantee, while significantly reducing driving comfort and severely impacting the user's driving experience, failing to meet the intelligent and human-centered development needs of smart cars.

[0026] Therefore, this invention provides an intelligent vehicle energy consumption management method. In response to the problems in the prior art such as inaccurate vehicle range estimation, lack of effective protection solutions in low energy conditions, and poor passive energy saving effect for drivers, it proposes a full-process, intelligent energy consumption management strategy to alleviate users' range anxiety for the "last leg of the journey" and achieve the ultimate guarantee of returning home for new energy intelligent vehicles.

[0027] Example 1 like Figure 1 As shown, this embodiment provides an intelligent vehicle energy consumption management method, which mainly includes the following steps: Based on the vehicle's current remaining available energy, current average energy consumption, and current location, determine whether to activate the range protection mode; When the range protection mode is activated, the vehicle is divided into multiple road segments between its current location and destination. The total energy consumption budget is calculated based on the vehicle's remaining available energy. With the constraint of not exceeding the total energy consumption budget, the maximum energy consumption allowed for each road segment and the corresponding recommended speed are calculated, thus forming the path with the lowest total energy consumption. Based on the obtained path, control the vehicle to drive at the recommended speed on the corresponding road segment.

[0028] The core purpose of the above method in this embodiment is to activate the range guarantee mode for scenarios where the vehicle's remaining energy is insufficient or just enough to support reaching the preset target location. By taking over vehicle speed control and overall vehicle energy consumption management, it calculates an energy-optimal driving strategy to maximize range under extreme conditions, ensuring that the vehicle can safely reach its destination and alleviating the user's range anxiety for the "last leg of the journey".

[0029] The above solution can be integrated as a software module into the central domain controller (Domain Controller) or vehicle control unit (VCU) of an intelligent vehicle, or it can exist as a standalone connected controller (T-Box). Its hardware foundation includes: a processing unit: a microprocessor with sufficient computing power (such as an ARM Cortex-A series chip) for running complex real-time algorithms; a storage unit: used to store map data, vehicle energy consumption models, historical data, and system programs; and communication interfaces: CAN / CAN FD / LIN bus interfaces for communicating with internal vehicle nodes such as the VCU, battery management system (BMS), engine ECU, body control module (BCM), and air conditioning controller to acquire data and send control commands.

[0030] The vehicle-mounted Ethernet interface is used for high-speed data exchange with the Advanced Driver Assistance Systems (ADAS) and infotainment systems. A GNSS receiver (GPS / BeiDou, etc.) is used to acquire the vehicle's high-precision real-time location and speed. A 4G / 5G cellular communication module is used to obtain real-time traffic conditions (TMC), weather information (wind speed, temperature), and map updates from the cloud. The software architecture is based on the AUTOSAR standard or a similar automotive software framework, with major functional modules existing as software components (SWCs) and interacting through a runtime environment (RTE).

[0031] The method will be explained in detail below.

[0032] S1: Trigger condition monitoring and judgment.

[0033] Continuously monitor the vehicle's current remaining available energy, current average energy consumption, and current location; where the vehicle's current remaining available energy includes the remaining battery charge and / or remaining fuel. Estimate the current driving range based on the vehicle's current remaining available energy and the vehicle's current average energy consumption; Calculate the remaining distance based on the vehicle's current location and destination; Preset critical threshold (e.g., 20 km); If the current driving range is less than the sum of the remaining distance and the critical threshold, the user will be prompted whether to activate the battery life protection mode.

[0034] Specifically: (1) Data acquisition: Continuously read the remaining battery charge (SOC) from the BMS, the remaining fuel from the fuel sensor unit, and the current average energy consumption (kWh / 100km or L / 100km) from the VCU via the CAN bus.

[0035] (2) Range calculation: Estimate the current range based on the vehicle's current remaining available energy and the vehicle's current average energy consumption; Range (km) = Vehicle's current remaining available energy (kWh or L) / Vehicle's current average energy consumption * 100.

[0036] (3) Critical judgment: The navigation system obtains the remaining distance D from the vehicle's current location to the preset destination. home .

[0037] A dynamic critical threshold T is set. This threshold is not a fixed value, but can be finely adjusted according to factors such as ambient temperature (low temperature affects battery performance) and average vehicle speed.

[0038] If the current driving range is less than the sum of the remaining distance and the critical threshold, the user will be prompted whether to activate the range protection mode; T can be initialized to 20 kilometers, or dynamically adjusted to 30 kilometers or 50 kilometers as needed, without limitation.

[0039] (4) User interaction: When the conditions are met, a prompt will pop up on the instrument panel or central control screen through the human-computer interaction module: "The remaining energy may not be able to reach the destination. Do you want to enable the range protection mode?" and provide "yes" and "no" options.

[0040] S2: Battery life protection mode activated.

[0041] After receiving user confirmation (via touchscreen, voice, or steering wheel buttons), the battery life protection mode is activated. At this time, the final navigation destination is forcibly locked to the user's preset destination, and any other original route planning is abandoned. Simultaneously, a mode status message is sent to the vehicle network, notifying other controllers (such as the air conditioning and entertainment systems) that the system is about to enter a low-energy operation state.

[0042] S3: Dynamic energy consumption limit calculation and path planning.

[0043] The distance between the vehicle's current location and its destination is divided into N road segments based on road conditions and road type (highway, city, congested, smooth). The total energy consumption budget is calculated based on the vehicle's current remaining available energy. Total energy consumption budget = vehicle's current remaining available energy * conversion efficiency - set safety redundancy. Using algorithms such as Dynamic Programming or Model Predictive Control (MPC), with the constraints of total energy consumption not exceeding the total energy consumption budget and reaching the destination, and with travel time or comfort as the optimization objective (lower priority), the maximum allowable energy consumption and the corresponding optimal recommended speed for each road segment are calculated in reverse. This process is essentially about allocating limited total energy to each road segment.

[0044] After planning, the energy consumption of multiple paths may be calculated simultaneously, and the path with the lowest total energy consumption may be selected, even if it is not the fastest.

[0045] In addition, the recommended speed curve (usually the economic speed range) and maximum speed limit that the vehicle needs to follow in order to achieve this energy consumption target can be recalculated.

[0046] During this process, real-time navigation data is acquired, including path distance, real-time traffic conditions, road type, slope, altitude change, predicted wind speed, temperature, and other information. This data is then combined with the vehicle's own energy consumption model, such as wind resistance, rolling resistance, and electric drive / engine efficiency MAP at different vehicle speeds, to perform reverse and precise calculations.

[0047] Specifically: 1. Road segment division.

[0048] (1) Triggering conditions: After starting the endurance guarantee mode, the road segmentation process is automatically triggered. The segmentation is completed based on the vehicle's current GNSS positioning coordinates as the starting point and the user's preset destination as the ending point, relying on real-time navigation data.

[0049] (2) Division basis: The division principle is based on the consistency of road conditions and the uniformity of road types to ensure that the driving conditions (resistance, energy consumption characteristics) in each road segment are relatively stable, and to avoid deviations in energy consumption calculation due to the large span of road segments.

[0050] The specific dimensions for classification include: Road types: Five core types are clearly distinguished: expressways, urban expressways, urban ordinary roads, rural roads, and mountain roads. The basic energy consumption characteristics (such as speed limits and road surface friction coefficients) of different types of roads vary greatly, and they are divided into different road sections.

[0051] Real-time traffic conditions: Under the same road type, the traffic conditions are further subdivided into congestion (speed ≤ 20km / h), slow traffic (20km / h < speed ≤ 40km / h), and smooth traffic (speed > 40km / h). For congested road sections, the energy consumption loss due to frequent starts and stops needs to be taken into account.

[0052] Special road conditions: Road sections with slope (absolute slope value ≥3°) and elevation changes (elevation difference ≥50m) are classified as independent road sections. The gravity resistance and power demand of such road sections are significantly different from those of flat roads, and energy consumption needs to be calculated separately.

[0053] (3) Road segment parameter recording: After the division is completed, a unique identifier is assigned to each road segment, and the core parameters of each road segment are recorded: road segment length, road type, real-time road condition level, slope, altitude change value, and current speed limit, so as to provide basic data for subsequent energy consumption calculation.

[0054] 2. Total energy consumption budget calculation.

[0055] Total energy consumption budget is the core constraint for energy allocation on subsequent road sections. It needs to be accurately quantified by combining vehicle remaining energy, energy conversion efficiency, and safety redundancy to avoid energy shortages or waste.

[0056] Specifically: Total energy consumption budget = Vehicle's current remaining available energy * Conversion efficiency - Set safety redundancy.

[0057] Among them, the vehicle's current remaining available energy is collected in real time through the vehicle's CAN bus. For pure electric vehicles, it is the remaining battery charge, and for hybrid electric vehicles, it is the sum of the remaining battery charge and the fuel convertible energy (fuel convertible energy = remaining fuel quantity × fuel calorific value × engine thermal efficiency).

[0058] The energy conversion efficiency is pre-stored in the vehicle system and dynamically called according to the vehicle's power type. The value is 85%-90% for pure electric vehicles (electric drive system) and 75%-80% for hybrid electric vehicles (engine + electric drive). It can be dynamically fine-tuned by ±3% according to the vehicle's real-time operating conditions (such as low temperature environment).

[0059] To avoid energy depletion due to sudden operating conditions (such as sudden traffic jams or sudden increases in wind speed), the reserved safety redundancy is set at 5%-8% of the vehicle's current remaining available energy. The less remaining energy, the higher the redundancy ratio (e.g., when the vehicle's current remaining available energy is ≤10%, the safety redundancy is 8%).

[0060] 3. Multi-source data fusion: The accuracy of energy consumption calculation relies on the real-time acquisition and fusion of multi-source data. Three types of core data are collected simultaneously to ensure data timeliness and accuracy. The specific data sources, acquisition frequency, and uses are as follows: (1) Navigation and environmental data: By using high-precision maps in the cloud, real-time navigation platforms, and vehicle-mounted environmental sensors, data such as path distance, real-time road condition level, road slope, altitude change, predicted wind speed (updated once every 1 minute within the next 10 minutes), and ambient temperature (collected once every 1 minute) are obtained to calculate road segment driving resistance (wind resistance, slope resistance) and the impact of the environment on energy consumption (such as low temperature leading to increased battery energy consumption).

[0061] (2) Positioning data: The vehicle's current coordinates, driving direction, altitude, and driving speed (collected once every 0.5 seconds) are obtained through GNSS positioning module (combined with Beidou + GPS dual-mode positioning) and vehicle inertial navigation module, etc., to accurately locate the road segment position, assist in calculating altitude changes and driving trajectory, and ensure the accuracy of road segment division and route planning.

[0062] (3) Real-time vehicle data: The current vehicle speed, acceleration, battery SOC (remaining power), electric drive / engine output power, air conditioning power, tire pressure and other data are obtained through the vehicle CAN bus. This data is used to update the vehicle energy consumption status in real time, correct the energy consumption model parameters, and ensure that the energy consumption calculation is consistent with the actual vehicle status.

[0063] (4) Data fusion processing: The Kalman filter algorithm is used to denoise and synchronize the multi-source data (unify the timestamp), remove abnormal data (such as positioning deviation and sensor fault data), and output standardized fused data for subsequent energy consumption calculation and algorithm optimization.

[0064] 4. Energy consumption model retrieval and correction. The energy consumption model is pre-stored in the system and is built based on the actual measured data of the vehicle model. It can be dynamically corrected according to real-time operating conditions to ensure the accuracy of energy consumption calculation.

[0065] (1) The vehicle's energy consumption MAP (multidimensional lookup table) was obtained through actual vehicle testing before leaving the factory. It covers the instantaneous energy consumption rate under different operating conditions. The core parameters are as follows: Input parameters (5 dimensions): vehicle speed V (km / h, range 0-120), acceleration a (m / s², range -5~5), gradient θ (°, range -15~15), air conditioning power (kW, range 0-3), tire pressure (bar, range 2.2-2.8). Output parameter: Instantaneous energy consumption rate P (kW) of the drive system, which is the energy consumption per unit time.

[0066] (2) For each segment after division, based on the fused data of the segment (vehicle speed, gradient, air conditioning power, etc.), query the corresponding instantaneous energy consumption rate P in the energy consumption MAP map as the basis for the energy consumption calculation of the segment.

[0067] (3) Dynamic correction: Based on the real-time energy consumption data of the vehicle (collected by CAN bus), the P obtained by query is dynamically corrected. The correction coefficient K = actual energy consumption rate / query energy consumption rate. If K deviates from 1 ± 0.1, the corresponding parameters of the MAP map are automatically adjusted to ensure that the subsequent energy consumption calculation error is ≤ 5%.

[0068] 5. Road segment energy consumption allocation and optimal vehicle speed calculation based on intelligent algorithms.

[0069] Dynamic Programming (DP) or Model Predictive Control (MPC) algorithms are used (which can be dynamically switched according to the vehicle's computing power: MPC is used when the computing power is ≥200 TOPS, and DP is used when the computing power is <200 TOPS) to realize the allocation of road segment energy consumption and the calculation of optimal vehicle speed under total energy consumption constraints.

[0070] (1) Constraints: The sum of energy consumption of all road segments ≤ total energy consumption budget; vehicles must reach their destination (the sum of the total length of road segments = the total distance from the starting point to the end point); the driving speed of each road segment ≤ the speed limit of that road segment, and ≥ the minimum safe speed (urban roads ≥ 10km / h, highways ≥ 60km / h).

[0071] (2) Optimization objectives: The primary objective (core) is to minimize total energy consumption; the secondary objective (secondary) is to minimize travel time and maximize driving comfort (comfort is measured by the rate of change of acceleration, ≤0.5m / s³).

[0072] (3) Basic data: fused data of each road segment, instantaneous energy consumption rate P output by the energy consumption model, road segment length L, etc.

[0073] (4) Calculation process (taking DP algorithm as an example): Taking the destination as the end point (the end point of the Nth segment), we work backwards to the starting point (the starting point of the 1st segment), and define the state variable of each segment as the remaining energy consumption at the starting point of that segment. For the i-th road segment (i ranges from N to 1), iterate through all possible driving speeds for the segment (within the speed limit) and calculate the segment energy consumption Ei for each speed (Ei = P × travel time, travel time = segment length L / speed). With the constraint that the remaining energy consumption is ≥0, the feasible speed range of each road segment is selected, the cumulative energy consumption (total energy consumption from the i-th road segment to the N-th road segment) corresponding to each feasible speed is calculated, and the speed with the minimum cumulative energy consumption is selected as the optimal recommended speed for that road segment. Simultaneously calculate the maximum allowable energy consumption of the road segment corresponding to the optimal vehicle speed to ensure that the energy consumption allocation of each road segment meets the total budget constraint.

[0074] (5) Simultaneously plan multiple alternative routes, calculate the total energy consumption and travel time for each route, and finally select the optimal route according to the following rules: Primary screening criterion: Total energy consumption ≤ Total energy consumption budget; paths that do not meet this criterion will be eliminated directly. Secondary selection criteria: Among the paths that meet the primary criteria, select the path with the lowest total energy consumption; if the difference in total energy consumption between two paths is ≤2%, select the path with shorter travel time and higher comfort.

[0075] After the selection is completed, the optimal path is automatically locked, and the optimal recommended speed and maximum allowable energy consumption of all road segments under that path are stored as the core basis for subsequent vehicle control.

[0076] In addition, based on the optimal route segments and the optimal recommended speed, a recommended speed curve and maximum speed limit for the whole vehicle are generated to ensure that the vehicle drives according to the optimal energy consumption strategy.

[0077] Specifically: Recommended speed curve generation: The optimal recommended speeds for each road segment are smoothly connected (using a linear interpolation algorithm) to avoid sudden speed changes (acceleration change rate ≤ 0.5 m / s³), generating a continuous speed-time curve (horizontal axis is travel time, vertical axis is recommended speed). This curve prioritizes the vehicle's economical speed range (60-80 km / h for pure electric vehicles, 50-70 km / h for hybrid vehicles).

[0078] Maximum speed limit setting: Based on the speed limit of each road segment and the optimal energy consumption requirements, the maximum speed limit of the whole vehicle is set to be less than or equal to the minimum speed limit of each road segment, and less than or equal to the economic speed limit of the vehicle model (to ensure the lowest energy consumption); if the remaining energy is extremely tight, it will be further reduced to the lower limit of the economic speed.

[0079] Finally, the recommended speed curve, maximum speed limit, and energy consumption distribution data for each road segment will be simultaneously output to the vehicle power control system (electric drive / engine) and the in-vehicle display system, which will be used for automatic vehicle speed control and displayed to the driver.

[0080] The method described in this embodiment offers more accurate range estimation and route planning, and more scientific energy consumption control. Unlike existing technologies that rely on rough estimations based on historical average energy consumption, this method combines core data such as the vehicle's current remaining available energy, real-time average energy consumption, and current location, while also considering variables such as real-time road conditions, environmental factors, and dynamic driving paths. Through segmented planning, the total energy consumption budget is rationally allocated to each road segment, calculating the maximum allowable energy consumption and corresponding recommended speed for each segment. This ultimately forms the optimal driving path with the lowest total energy consumption, ensuring a high degree of match between energy consumption estimation and actual driving needs, avoiding energy waste or insufficient energy due to estimation errors. For scenarios where the vehicle's remaining energy is insufficient or just enough to reach a preset destination (such as home, a charging station, or other priority destinations), a range guarantee mode is activated. Through systematic energy consumption calculation and vehicle control, this ensures the vehicle can safely and stably reach its destination, alleviating range anxiety for users on the "last leg" of their journey and achieving ultimate homecoming assurance for new energy intelligent vehicles.

[0081] S4: Active speed and energy consumption control.

[0082] 1. Vehicle speed control: Through the vehicle CAN bus or other control network, take priority over the cruise control system (ACC / cruise control) or drive torque control, and send target control commands to the adaptive cruise control system (ACC) or vehicle control unit (VCU) to control the actual vehicle speed below the recommended speed or the maximum speed limit.

[0083] This process can be advisory (prompting the driver to maintain a specific speed) or mandatory (automatically controlling the speed).

[0084] (1) Suggestion: Use HMI graphics and sound to prompt the driver to keep the vehicle speed within the designated green zone.

[0085] Specifically: For example, the HMI graphic prompts: the instrument panel and the central control screen simultaneously display the green speed range (such as 60-70km / h), and the current actual speed is marked with different colors (green = meets the requirements, yellow = slightly higher than the recommended range, red = exceeds the maximum speed limit), while displaying the text prompt "Please keep the speed in the green range to save energy". Audio prompt: When the actual vehicle speed deviates from the recommended range by ±5km / h, a voice prompt will be triggered (if the vehicle speed is too high, it is recommended to reduce it to below 65km / h). The voice volume should be moderate (not higher than 60dB) to avoid interfering with the driver. Tactile cue: Optional slight vibration of the steering wheel (vibration frequency 5Hz, amplitude ≤0.5mm), which is triggered only when the vehicle speed exceeds the maximum speed limit to remind the driver to slow down.

[0086] (2) Mandatory / Automatic: The VCU directly intervenes in the vehicle's power output, limiting the output torque of the drive motor or the throttle opening of the engine, so that the actual vehicle speed cannot exceed the recommended speed range and the maximum speed limit, while avoiding the vehicle speed from falling below the minimum safe speed.

[0087] Specifically: Pure electric vehicles: A torque limiting command is sent to the VCU, and the maximum output torque of the drive motor is dynamically adjusted according to the deviation between the actual vehicle speed and the recommended vehicle speed: When the actual vehicle speed is less than or equal to the lower limit of the recommended vehicle speed, the torque is not limited (ensuring normal acceleration); when the actual vehicle speed is within the recommended range, the torque is maintained within the economic output range; when the actual vehicle speed is greater than or equal to the upper limit of the recommended vehicle speed, the torque is gradually reduced (the reduction increases with the increase of the deviation) until the vehicle speed falls back to the recommended range; if the vehicle speed exceeds the maximum speed limit, the torque is immediately limited to the minimum value that only maintains constant speed driving (ensuring no speeding).

[0088] Hybrid vehicles: Simultaneously send instructions to the VCU and engine controller to limit the engine throttle opening (maximum opening not exceeding 60%), while optimizing the power distribution between the engine and electric drive, prioritizing the use of electric drive mode (lower energy consumption), starting the engine only when climbing hills or accelerating rapidly (necessary conditions), and controlling the engine speed within the economic speed range (1500-2500rpm) to avoid high speed and high energy consumption.

[0089] Special operating condition adaptation: When encountering emergency overtaking, hazard avoidance and other scenarios, if the driver presses the accelerator pedal deeply (throttle opening ≥ 80%), the mandatory speed control will be temporarily released, allowing the vehicle to accelerate briefly; after the overtaking is completed (throttle opening ≤ 50%, lasting 2 seconds), the mandatory control will be automatically restored to ensure driving safety in emergency scenarios.

[0090] 2. Vehicle-wide Energy Management: Commands are sent to relevant controllers (such as HVAC controllers and BCMs) via the CAN / LIN bus to manage the power consumption of each electrical appliance in a tiered manner. Under the premise of ensuring safety, the power of unnecessary high-energy-consuming loads is automatically reduced or shut down. The control objective is to ensure that the real-time energy consumption of the entire vehicle is lower than the dynamically updated segmented energy consumption upper limit calculated in step 3.

[0091] Specifically: (1) Level 1 restrictions (automatic execution): reduce the power of the air conditioning compressor, turn off the seat heating / ventilation, steering wheel heating, reduce the brightness of the headlights (within the scope of safety regulations), etc.

[0092] Example as follows: (1-1) Air Conditioning System (HVAC Controller): Example of control command 1 (cooling mode): Send a command to the HVAC controller to adjust the air conditioner compressor's operating mode from maximum cooling to economy cooling, and reduce the compressor speed from 3000rpm to 1800rpm; at the same time, adjust the set temperature to the ambient temperature (summer: current setting 22℃ → adjust to 25℃; winter heating: current setting 26℃ → adjust to 23℃), reducing the compressor load, which is expected to reduce air conditioner power consumption by 30%-40%.

[0093] Control command example 2 (dehumidification mode): Turn off the air conditioning compressor and only turn on the blower (fan speed set to level 2) to dehumidify using the vehicle dehumidification module, avoiding high energy consumption caused by continuous compressor operation; if the humidity is ≥80%, start the compressor again (low speed 1500rpm).

[0094] (1-2) Seat / steering wheel heating / ventilation: Send commands to the seat controller and steering wheel controller to directly turn off the seat heating / ventilation and steering wheel heating functions (regardless of whether they are currently on); if the ambient temperature is extremely low (≤-5℃), the lowest seat heating setting (power ≤50W) can be retained to ensure basic comfort.

[0095] (1-3) Lighting system (BCM body controller): Sends instructions to the BCM to reduce the headlight brightness from 100% to 70% (meets relevant requirements and does not affect nighttime driving visibility); automatically turns off the interior ambient lights, welcome lights, and trunk lights (temporarily turned on when unlocking, and automatically turned off 30 seconds after unlocking); daytime running lights are turned on normally (safety first).

[0096] (1-4) Other auxiliary electrical appliances: automatic window closing and anti-pinch function, automatic folding function of rearview mirror (manual control only) to reduce the power consumption of the vehicle body controller.

[0097] (2) Level 2 restrictions (prompt users): It is recommended that users turn off the in-vehicle entertainment system, some screens, etc.

[0098] Specifically as follows: (2-1) In-vehicle infotainment system: Sends a command request to the infotainment system controller and prompts the driver through the HMI that "current energy consumption is high, it is recommended to turn off the passenger screen / reduce the brightness of the main screen"; if the driver confirms, the system will automatically reduce the brightness of the main screen from 100% to 50% and turn off the passenger screen and the rear entertainment screen, which is expected to reduce power consumption by 10-15W.

[0099] (2-2) Other non-essential electrical appliances: The HMI displays "It is recommended to turn off external devices such as the vehicle charger and vehicle refrigerator to further save energy consumption" and displays the real-time power consumption of each external device for the driver's reference. After the driver manually turns them off, the device status is confirmed through the CAN bus and the vehicle energy consumption data is updated. If the driver refuses, the device will not be forcibly turned off, but the energy consumption will be continuously monitored.

[0100] This embodiment actively intervenes in vehicle control to maximize the vehicle's maximum range potential, breaking away from the passive mode of existing technologies that only warn and do not intervene. After the range protection mode is activated, it actively takes over vehicle speed control and overall vehicle energy consumption management. Through precise intelligent decision-making, it optimizes energy-related modules such as vehicle power output and air conditioning use under the vehicle's extreme energy state, maximizing the vehicle's range potential. This ensures that the vehicle can reach the preset safe destination first, while minimizing the impact on the driving experience, achieving a balance between energy saving and comfort.

[0101] S5: Dynamic updates and feedback.

[0102] Throughout the journey, the system continuously monitors actual energy consumption, road condition changes, and remaining available energy in real time. Steps S3 and S4 are executed cyclically at a set frequency (e.g., every 30 seconds or every kilometer traveled) to dynamically update the optimal route, recommended speed, and energy consumption allocation strategy. This is because actual road conditions may change suddenly (e.g., severe congestion ahead) or actual energy consumption may deviate from the predicted value. Through closed-loop feedback, the plan can be continuously corrected.

[0103] Meanwhile, a display area on the dashboard clearly shows key information (such as estimated remaining range and current energy-saving measures) to the user. For example, a dynamic display might show: "Range Protection Mode - Estimated Remaining Range: XX km - Current Energy-Saving Measures: Air Conditioning Economy Mode".

[0104] S6: Mode Deactivation: When the vehicle safely arrives at the preset destination, or when the user manually forces the exit from this mode, the range protection mode is deactivated, and the vehicle control system returns to normal.

[0105] The following is an example of a running scenario.

[0106] A pure electric vehicle is driving on the highway with 20% battery remaining, a displayed range of 150 kilometers, and 120 kilometers to its destination. Based on real-time road conditions (long uphill climb and slow traffic ahead), the system determines the initial threshold and prompts the user to activate the vehicle.

[0107] After activation: Calculations show that maintaining the current speed of 120km / h will result in excessive energy consumption. Therefore, the vehicle speed is forcibly limited to the economical speed of 90km / h.

[0108] En route: Increased congestion ahead detected, immediate recalculation. To cope with slow crawling in congested sections, the air conditioning setting temperature was further increased, and the recommended speed was reduced to 60km / h, so that more energy could be allocated to low-speed sections.

[0109] Ultimately, the vehicle arrived safely at the home garage with a safety margin of 3% remaining battery power.

[0110] The method described in this embodiment is highly intelligent, adaptable to various driving scenarios, and highly practical. Its energy consumption management strategy has dynamic adjustment capabilities, which can dynamically optimize the energy consumption distribution and recommended speed of road segments based on real-time changes in road conditions, environment, and remaining energy during driving. It is suitable for various complex driving scenarios such as urban congestion, highway driving, and mountain roads. At the same time, its automated start-up and control logic does not require the driver to have professional energy-saving driving experience, making it easy to operate. It can be widely used in various hybrid and pure electric intelligent vehicles and has extremely high industrial application value.

[0111] In summary, the method of this embodiment has the following advantages: Active safety protection: Transforming passive warnings into proactive protection, fundamentally avoiding the risk of breaking down on the road due to energy depletion, and improving driving safety and user experience.

[0112] Energy Consumption Limit Optimization: By integrating real-time road conditions, vehicle models, and global planning, it achieves refined energy consumption management that surpasses that of human drivers, maximizing range under extreme conditions.

[0113] Intelligent collaborative control: Innovatively, navigation planning, vehicle speed control and vehicle energy consumption management (power system + electrical appliances) are collaboratively optimized to form a complete energy security closed-loop system.

[0114] User peace of mind: Reduces the psychological pressure and operational burden on users when the battery / fuel level is low, alleviating range anxiety for users on the "last leg of the journey".

[0115] Example 2 This embodiment provides an intelligent vehicle energy consumption management system, including: The judgment module is configured to determine whether to activate the range protection mode based on the vehicle's current remaining available energy, the vehicle's current average energy consumption, and the vehicle's current location. The planning module is configured to divide the vehicle's current location and destination into multiple road segments when the range protection mode is activated. It calculates the total energy consumption budget based on the vehicle's current remaining available energy, and calculates the maximum energy consumption allowed for each road segment and the corresponding recommended speed, with the constraint of not exceeding the total energy consumption budget, thereby forming the path with the lowest total energy consumption. The control module is configured to control the vehicle's movement at a recommended speed on the corresponding road segment based on the obtained path.

[0116] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0117] In further embodiments, the following is also provided: An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0118] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0119] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0120] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0121] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0122] A computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0123] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0124] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0125] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0126] Those skilled in the art will recognize that the units and algorithm steps described in connection with the various examples of this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0127] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for intelligent vehicle energy consumption management, characterized in that, include: Based on the vehicle's current remaining available energy, current average energy consumption, and current location, determine whether to activate the range protection mode; When the range protection mode is activated, the vehicle is divided into multiple road segments between its current location and destination. The total energy consumption budget is calculated based on the vehicle's remaining available energy. With the constraint of not exceeding the total energy consumption budget, the maximum energy consumption allowed for each road segment and the corresponding recommended speed are calculated, thus forming the path with the lowest total energy consumption. Based on the obtained path, control the vehicle to drive at the recommended speed on the corresponding road segment.

2. The intelligent vehicle energy consumption management method as described in claim 1, characterized in that, The process of determining whether to activate the range protection mode includes: calculating the current driving range based on the vehicle's current remaining available energy and the vehicle's current average energy consumption; calculating the remaining distance based on the vehicle's current location and destination; setting a preset critical threshold; and prompting the user whether to activate the range protection mode if the current driving range is less than the sum of the remaining distance and the critical threshold.

3. The intelligent vehicle energy consumption management method as described in claim 2, characterized in that, After obtaining user confirmation to activate the battery life protection mode, the final navigation destination is forcibly locked to the preset destination, and any other original route planning is abandoned.

4. The intelligent vehicle energy consumption management method as described in claim 1, characterized in that, The total energy consumption budget is calculated based on the vehicle's current remaining available energy. Total energy consumption budget = vehicle's current remaining available energy * conversion efficiency - set safety redundancy.

5. The intelligent vehicle energy consumption management method as described in claim 1, characterized in that, During vehicle control, the speed control process includes: taking over the cruise control system or drive torque control, sending target control commands to the cruise control system or vehicle controller via the CAN bus, and controlling the actual vehicle speed below the recommended speed or maximum speed limit.

6. The intelligent vehicle energy consumption management method as described in claim 1, characterized in that, During vehicle operation, energy management includes: classifying and managing the power consumption of various electrical appliances, and automatically reducing or shutting down the power of unnecessary high-energy-consuming loads while ensuring safety.

7. An intelligent vehicle energy consumption management system, characterized in that, include: The judgment module is configured to determine whether to activate the range protection mode based on the vehicle's current remaining available energy, the vehicle's current average energy consumption, and the vehicle's current location. The planning module is configured to divide the vehicle's current location and destination into multiple road segments when the range protection mode is activated. It calculates the total energy consumption budget based on the vehicle's current remaining available energy, and calculates the maximum energy consumption allowed for each road segment and the corresponding recommended speed, with the constraint of not exceeding the total energy consumption budget, thereby forming the path with the lowest total energy consumption. The control module is configured to control the vehicle's movement at a recommended speed on the corresponding road segment based on the obtained path.

8. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-6.

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