Soc optimization method, system, and vehicle

Abstract

The embodiment of the present application relates to the battery technical field, disclose a kind of SOC optimization method, system and vehicle, the method comprises: obtaining current vehicle state data and path planning information, current vehicle state data at least includes current SOC value;The SOC consumption value of power battery is predicted based on the path planning information if pure electric driving to destination, and according to current SOC value, SOC consumption value calculates terminal SOC value;The terminal SOC value is compared with the SOC lower limit threshold value, if terminal SOC value is less than or equal to SOC lower limit threshold value, then in first cut-in time point engine is started, enters hybrid drive mode, to provide driving force for vehicle while charging power battery, maintain the SOC value of power battery above the SOC lower limit threshold value.The present application can accurately identify the start-stop time of engine, to ensure that the best balance between vehicle economy and power is realized.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and more specifically to a SOC optimization method, system, and vehicle. Background Technology

[0002] Hybrid electric vehicles (HEVs) have become an important direction in current automotive technology development due to their combination of the advantages of internal combustion engine vehicles and pure electric vehicles, such as the absence of range anxiety and relatively low overall vehicle cost. However, hybrid systems based on HEV configurations (especially parallel or series-parallel configurations) are typically equipped with small-capacity power batteries, which leads to a significant technical drawback: when the battery's state of charge (SOC) is low, the electric motor cannot provide sufficient auxiliary power, resulting in a sharp decline in the vehicle's power performance and severely impacting the driving experience.

[0003] Most existing energy management strategies employ rule-based or instantaneous optimization algorithm-based control strategies. Their decisions primarily rely on the current vehicle state (such as vehicle speed, acceleration, and battery SOC), lacking forward-looking perception of future driving conditions. This can lead to inappropriate engine start-stop timing, failing to achieve the optimal balance between vehicle economy and power.

[0004] Therefore, it is necessary to develop a new SOC optimization method, system, and vehicle. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this application is to provide a SOC optimization method, system and vehicle that can accurately identify the start-stop time of the engine to ensure the best balance between vehicle economy and power.

[0006] In a first aspect, embodiments of this application provide a SOC optimization method, comprising the following steps: Obtain current vehicle status data and route planning information. The current vehicle status data includes at least the current SOC value, where SOC is the battery state of charge. Based on the route planning information, the SOC consumption value of the power battery is predicted when the entire journey is driven in pure electric mode to the destination, and the final SOC value is calculated based on the current SOC value and the SOC consumption value. The endpoint SOC value is compared with a preset lower limit threshold SOC. If the final SOC value is less than or equal to the lower SOC threshold, the first entry point for entering the hybrid drive mode is determined, and the engine is started at the first entry point to enter the hybrid drive mode, so as to charge the power battery while providing driving force to the vehicle, and maintain the SOC value of the power battery above the lower SOC threshold.

[0007] In the above technical solution, the SOC optimization method of this invention predicts the pure electric SOC consumption value throughout the journey through real-time path planning information, and determines in advance the relationship between the final SOC value and the lower limit threshold of SOC. Compared with the traditional passive method of starting the engine only when the SOC value is lower than a fixed threshold, this invention can immediately or in advance start the engine to enter the hybrid drive mode when the final SOC value is ≤ the lower limit threshold of SOC, actively avoiding the risk of SOC falling into the low power range, avoiding limited motor output and reduced acceleration performance, ensuring stable power in scenarios such as climbing and overtaking, solving the pain point of sudden power drop in traditional control, and thus taking into account both the economy and power of the vehicle.

[0008] One possible implementation method for predicting the SOC consumption value is as follows: The route planning information includes at least the remaining total driving distance and the slope information of the road ahead; Based on the remaining total driving distance and the slope information of the road ahead, combined with the vehicle dynamics model, the SOC consumption value of the power battery is predicted when the entire journey is undertaken in pure electric mode to the destination.

[0009] In the above technical solution, by using the remaining total driving distance and the slope information of the road ahead, and combining the vehicle dynamics model, the pure electric SOC consumption value of the whole journey is predicted, which provides data support for judging the relationship between the final SOC value and the lower limit threshold of SOC in advance.

[0010] One possible implementation method for setting the SOC lower limit threshold is as follows: Obtain vehicle operating parameters, assess power demand intensity based on vehicle operating parameters, and set the SOC lower limit threshold based on the power demand intensity.

[0011] In the above technical solution, the lower limit of SOC is linked to the driver's vehicle operation parameters. The power demand intensity is evaluated through the vehicle operation parameters, thereby realizing the dynamic adjustment of the lower limit of SOC.

[0012] One possible implementation is that the vehicle operating parameter is the current accelerator pedal opening, and the power demand intensity is evaluated based on the current accelerator pedal opening.

[0013] In the above technical solution, the proposed lower limit threshold of SOC is linked to the throttle opening, which can intelligently identify different driving styles of the driver (such as aggressive or mild). This enables the engine start-stop strategy to be dynamically optimized through real-time navigation and driver operation intentions (i.e. power demand), so that the SOC of the power battery is always maintained within the optimal range that can meet the expected power demand while taking into account economy.

[0014] One possible implementation method for determining the first entry point is as follows: The first entry SOC value is calculated as follows: The first input SOC value is greater than (the SOC value at departure + the lower limit of SOC) / 2; The first entry point is when the current SOC value reaches the first entry SOC value. In the above technical solution, the first entry SOC value is greater than the average of the SOC value at the start and the lower limit threshold of SOC, which can reserve a reasonable amount of power for vehicle charging.

[0015] One possible implementation also includes: If the difference between the endpoint SOC value and the lower limit threshold of SOC is greater than or equal to the first preset SOC threshold, then pure electric mode is used for driving.

[0016] In the above technical solutions, the pure electric mode is used first when the distance is short or when the battery is sufficient and the power demand is not high, which avoids the engine frequently starting and stopping or running in the inefficient zone and reduces fuel consumption.

[0017] One possible implementation also includes: If the SOC value at the start is greater than the second preset SOC threshold, and the difference between the SOC value at the end and the lower limit of SOC is greater than 0 but less than the first preset SOC threshold, then the second entry point for entering the hybrid drive mode is determined, and the hybrid drive mode is entered at the second entry point.

[0018] In the above technical solution, the timing of entry is determined by the difference between the SOC value at the start and the SOC value at the end, that is, the optimal engine start time is determined intelligently, so as to balance fuel economy and driving power throughout the entire journey.

[0019] One possible implementation method is as follows: The second entry point is determined as follows: The second entry SOC value is calculated as follows: Second entry SOC value = (SOC value at departure + SOC lower limit threshold) / 2; The second entry point is when the current SOC value reaches the second entry SOC value.

[0020] In the above technical solution, using the average of the initial SOC value and the lower limit SOC threshold as the second entry SOC value allows for a reasonable reserve of battery capacity for charging while driving. This method eliminates the need for complex calculations, quickly determines the entry point, and balances charging demand with range assurance, resulting in smoother mode switching.

[0021] Secondly, embodiments of this application provide a SOC optimization system deployed in a vehicle, including a memory and a processor. The memory is used to store a computer program, and the processor is used to call the computer program to execute the SOC optimization method described in this invention.

[0022] In the above technical solution, the SOC optimization system of this invention predicts the pure electric SOC consumption value throughout the journey through real-time path planning information, and determines in advance the relationship between the final SOC value and the lower limit threshold of SOC. Compared with the traditional passive method of starting the engine only when the SOC value is lower than a fixed threshold, this invention can immediately or in advance start the engine to enter the hybrid drive mode when the final SOC value is ≤ the lower limit threshold of SOC, actively avoiding the risk of SOC falling into the low power range, avoiding limited motor output and reduced acceleration performance, ensuring stable power in scenarios such as climbing and overtaking, solving the pain point of sudden power drop in traditional control, and ensuring the best balance between vehicle economy and power.

[0023] Thirdly, embodiments of this application provide a vehicle that includes the SOC optimization system described in this invention. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application will be described below.

[0025] Figure 1 This is a block diagram of a vehicle disclosed in an embodiment of this application; Figure 2 This is a block diagram of a SOC optimization system disclosed in an embodiment of this application; Figure 3 This is one of the flowcharts for a SOC optimization method disclosed in an embodiment of this application; Figure 4 This is a second flowchart of a SOC optimization method disclosed in an embodiment of this application; Explanation of reference numerals in the attached figures: 1-SOC optimization system; 11-Memory, 12-Processor, 2-Energy management system, 3-Power battery, 4-Generator, 5-Engine. Detailed Implementation

[0026] The embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The detailed description of the following embodiments and the accompanying drawings are used to illustrate the principles of this application by way of example, but should not be used to limit the scope of this application, that is, this application is not limited to the described embodiments.

[0027] Please see Figure 1 , Figure 1This is a schematic diagram of the vehicle structure disclosed in an embodiment of this application. The vehicle can be a hybrid electric vehicle (HEV). One vehicle includes a State of Charge (SOC) optimization system 1, an energy management system 2, a power battery 3, a generator 4, and an engine 5. The SOC optimization system 1 establishes a communication connection with the energy management system 2, and the energy management system 2 establishes communication connections with the engine 5, the generator 4, and the power battery 3 respectively. The engine 5 is connected to the generator 4, and the generator 4 is electrically connected to the power battery 3. The energy management system 2 coordinates the operation of the engine 5 and the power battery 3. The generator 4 converts the kinetic energy output by the engine 5 into electrical energy to charge the power battery 3.

[0028] Please see Figure 2 , Figure 2 This is a schematic diagram of the functional architecture of the SOC optimization system disclosed in this application embodiment, which is deployed in a vehicle. The SOC optimization system 1 includes a memory 11 and a processor 12. The memory 11 stores computer programs, and the processor 12 calls the computer programs to execute the SOC optimization method in this application embodiment. This SOC optimization system 1 predicts the pure electric SOC consumption value throughout the journey using real-time path planning information, and pre-determines the relationship between the final SOC value and the lower SOC threshold. Compared to the traditional passive approach of starting the engine 5 only when the SOC value is below a fixed threshold, this invention can immediately or pre-start the engine 5 to enter hybrid drive mode when the final SOC value is ≤ the lower SOC threshold. This proactively avoids the risk of SOC falling into the low power range, prevents limited motor output and decreased acceleration performance, ensures stable power in scenarios such as climbing and overtaking, and solves the pain point of sudden power drop in traditional control, thereby achieving a balance between fuel economy and driving power throughout the entire journey.

[0029] Please see Figure 3 , Figure 3 This is one of the flowcharts illustrating the SOC optimization method disclosed in this application. An SOC optimization method includes the following steps: The system acquires current vehicle status data and route planning information. The current vehicle status data includes at least the current State of Charge (SOC) value, where SOC is the battery's state of charge. Based on the route planning information, it predicts the SOC consumption of the power battery 3 when driving entirely on electric power to the destination. It then calculates the final SOC value based on the current SOC value and the SOC consumption value. The final SOC value is compared to a preset lower SOC threshold. If the final SOC value is less than or equal to the lower SOC threshold, the system determines the first entry point into the hybrid drive mode and starts the engine 5 at this first entry point to enter hybrid drive mode. This provides driving force to the vehicle while simultaneously charging the power battery 3, maintaining the SOC value of the power battery 3 above the lower SOC threshold.

[0030] The SOC optimization method provided in this application uses real-time path planning information obtained from the navigation system to predict the pure electric SOC consumption value throughout the journey and to determine the relationship between the final SOC value and the lower limit threshold in advance. Compared with the traditional passive approach of starting the engine 5 only when the SOC value is below a fixed threshold, this application can immediately or in advance start the engine 5 to enter the hybrid drive mode when the final SOC value is ≤ the lower limit threshold. This actively avoids the risk of the SOC falling into the low power range, avoids limited motor output and decreased acceleration performance, ensures stable power in scenarios such as climbing and overtaking, and solves the pain point of sudden power drop in traditional control. Thus, it achieves a balance between fuel economy and driving power throughout the entire journey. In one possible embodiment, the method for predicting SOC consumption values ​​is as follows: The route planning information includes at least the remaining total driving distance and the slope information of the road ahead. Based on the remaining total driving distance and the slope information of the road ahead, and combined with the vehicle dynamics model, the SOC consumption value of the power battery 3 is predicted when the entire journey is undertaken in pure electric mode. This application uses the remaining total driving distance and the slope information of the road ahead, combined with the vehicle dynamics model, to predict the SOC consumption value under pure electric mode, providing data support for predicting the relationship between the final SOC value and the lower limit threshold of SOC in advance.

[0031] For example, a vehicle dynamics model is used to calculate the total drag required for vehicle movement, using the following formula: F total =F rolling +F grade +F accel +F air Among them, F rolling For rolling resistance, F grade F represents the slope resistance (calculated from the road's slope information). accel To accelerate the drag (estimated from the average vehicle speed and acceleration predicted by the navigation system), F air This refers to air resistance.

[0032] After calculating the total resistance required for the vehicle to move, the total energy consumption and the corresponding SOC consumption can be estimated based on the total resistance and motor efficiency.

[0033] For example, the formula for calculating the endpoint SOC value is as follows: SOC end_predicted =SOC now -ΔSOC consumption .

[0034] Among them, SOC end_predicted The endpoint SOC value, SOC now The current SOC value, ΔSOC consumptionThis represents the SOC consumption value.

[0035] In one possible embodiment, the SOC lower limit threshold is set as follows: This application acquires vehicle operating parameters, assesses the intensity of power demand based on these parameters, and sets a lower limit threshold for State of Charge (SOC) based on this power demand intensity. By linking the lower limit threshold for SOC with the driver's vehicle operating parameters, the application assesses the driver's power demand intensity using these parameters, thereby achieving dynamic adjustment of the lower limit threshold for SOC.

[0036] In one possible embodiment, the vehicle operating parameter is the current accelerator pedal opening, and the power demand intensity is assessed based on the current accelerator pedal opening. The SOC lower limit threshold proposed in this application is linked to the accelerator pedal opening, which can intelligently identify different driving styles of the driver (such as aggressive or mild). This enables the formulation of an engine start-stop strategy based on real-time navigation and power demand, ensuring that the SOC value of the power battery 3 is within the user's expected range, achieving optimal power performance while meeting the user's fuel consumption requirements.

[0037] In one possible implementation, the intensity of power demand is assessed based on the current accelerator pedal opening, specifically as follows: The system has a pre-defined mapping relationship between accelerator pedal opening and power demand. By querying this mapping relationship based on the current accelerator pedal opening, the corresponding power demand can be obtained. This application, through the pre-defined mapping relationship between accelerator pedal opening and power demand, allows the system to quickly query the matching power demand based on the current accelerator pedal opening. It directly converts driver input into a clear power demand signal, reducing calculation delays, ensuring more timely power output response, and enabling more precise power adjustment, thus improving driving smoothness and handling experience.

[0038] Based on real-time data of the current accelerator pedal opening, the driver's power demand intensity is mapped. A lower limit threshold for State of Charge (SOC) is set to ensure power performance; this threshold is positively correlated with the accelerator pedal opening. That is, the larger the current accelerator pedal opening, the higher the driver's power demand. To ensure power response, a higher lower SOC threshold is required to avoid insufficient power due to inadequate SOC during periods of high power demand.

[0039] In one possible embodiment, the method for determining the first cut-in time point is as follows: The first entry SOC value is calculated as follows: The first cut-in SOC value is greater than (departure SOC value + SOC lower limit threshold) / 2. The first cut-in time point is when the current SOC value reaches the first cut-in SOC value. The first cut-in SOC value is greater than the average of the departure SOC value and the SOC lower limit threshold, reserving a reasonable amount of charge for vehicle charging. The departure SOC value is the current SOC value at the time of departure.

[0040] Please see Figure 4 , Figure 4 This is a second schematic flowchart of the SOC optimization method disclosed in this application. In one possible embodiment, the SOC optimization method further includes: if the difference between the endpoint SOC value and the lower limit threshold of SOC is greater than or equal to a first preset SOC threshold (exemplarily, the first preset SOC threshold can be set to 5%, which can be adjusted according to the actual vehicle configuration), it indicates that the remaining charge of the power battery 3 is sufficient to drive to the destination in pure electric mode, and the power performance throughout the journey can meet the expected needs, then pure electric mode is used. This application prioritizes the use of pure electric mode for short distances or when the charge is sufficient and the power demand is not high, avoiding frequent start-stop or operation of the engine 5 in the inefficient zone, thus reducing fuel consumption.

[0041] Please see Figure 4 In one possible embodiment, a SOC optimization method further includes: if the SOC value at the start is greater than a second preset SOC threshold (exemplarily, the second preset SOC threshold can be set to be greater than 90%, and the specific value can be calibrated based on battery capacity), and the difference between the SOC value at the end and the lower limit threshold of SOC is greater than 0 but less than a first preset SOC threshold, then a second entry point for entering the hybrid drive mode is determined, and the hybrid drive mode is entered at the second entry point to achieve a slight increase in the SOC value. This application determines the second entry point based on the difference between the SOC value at the start and the SOC value at the end, that is, it achieves intelligent determination of the optimal engine start time, thereby balancing fuel economy and driving power throughout the entire journey.

[0042] In one possible embodiment, the second cut-in time point is determined as follows: The second entry SOC value is calculated as follows: Second entry SOC value = (Departure SOC value + SOC lower limit threshold) / 2; the second entry point is when the current SOC value reaches the second entry SOC value. Using the average of the departure SOC value and the SOC lower limit threshold as the second entry SOC value allows for a reasonable amount of charge reserve during driving. This method eliminates the need for complex calculations, quickly determines the entry timing, and balances charging needs with range assurance, resulting in smoother mode switching.

[0043] During vehicle operation, the SOC prediction value and engine start-stop strategy are continuously optimized and corrected based on real-time updated vehicle status data, path planning information, and driver operation parameters to achieve adaptive control.

[0044] This application predicts the SOC consumption value of the power battery 3 when driving to the destination in pure electric mode using real-time route planning information (i.e., navigation information), and compares it with a dynamic lower limit threshold of SOC (i.e., power demand threshold). In other words, it combines real-time navigation information (such as remaining distance and gradient) with the driver's real-time power demand (reflected by the accelerator pedal opening) to proactively and dynamically formulate an engine start-stop strategy. This allows the engine 5 to be started in advance before the SOC value drops to the low power range, effectively avoiding the problem of reduced vehicle power caused by excessively low SOC and improving the driving experience.

[0045] This application prioritizes the use of pure electric mode when traveling short distances or when the battery is fully charged and the power demand is not high, thus avoiding frequent start-stop or operation of engine 5 in the inefficient zone and reducing fuel consumption.

[0046] The SOC lower limit threshold proposed in this application is linked to the accelerator pedal opening, which can intelligently identify different driving styles of the driver (such as aggressive or mild) and adjust the control strategy accordingly, thus achieving a personalized balance between power and economy.

[0047] This application is mainly based on existing vehicle sensor and navigation system data, and can be implemented through software algorithm upgrades without increasing new hardware costs, making it easy to industrialize.

[0048] In this embodiment, the computer program may include program code, which includes computer-executable instructions. Memory 11 may include high-speed RAM or non-volatile memory, such as at least one disk storage device. Processor 12 may be a central processing unit (CPU), a microcontroller unit (MCU), or an application-specific integrated circuit (ASIC).

[0049] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A SOC optimization method, characterized in that, Includes the following: Obtain current vehicle status data and route planning information. The current vehicle status data includes at least the current SOC value, where SOC is the battery state of charge. Based on the route planning information, predict the SOC consumption value of the power battery (3) when driving to the destination in pure electric mode, and calculate the destination SOC value based on the current SOC value and the SOC consumption value. The endpoint SOC value is compared with a preset lower limit threshold SOC. If the final SOC value is less than or equal to the lower limit threshold of SOC, then the first entry point into the hybrid drive mode is determined, and the engine (5) is started at the first entry point to enter the hybrid drive mode, so as to charge the power battery (3) while providing driving force to the vehicle, and maintain the SOC value of the power battery (3) above the lower limit threshold of SOC; wherein, the method for determining the first entry point is as follows: calculate the first entry SOC value, specifically: the first entry SOC value > (the SOC value at departure + the lower limit threshold of SOC) / 2; when the current SOC value reaches the first entry SOC value, it is the first entry point; If the SOC value at the start is greater than the second preset SOC threshold, and the difference between the SOC value at the end and the lower limit of SOC is greater than 0 but less than the first preset SOC threshold, then the second entry point for entering the hybrid drive mode is determined, and the hybrid drive mode is entered at the second entry point.

2. The SOC optimization method according to claim 1, characterized in that, The method for predicting the SOC consumption value is as follows: The route planning information includes at least the remaining total driving distance and the slope information of the road ahead; Based on the remaining total driving distance and the slope information of the road ahead, combined with the vehicle dynamics model, the SOC consumption value of the power battery (3) is predicted when the vehicle travels to the destination in pure electric mode.

3. The SOC optimization method according to claim 1, characterized in that, The method for setting the lower limit threshold of SOC is as follows: Obtain vehicle operating parameters, assess power demand intensity based on vehicle operating parameters, and set the SOC lower limit threshold based on the power demand intensity.

4. The SOC optimization method according to claim 3, characterized in that, The vehicle operating parameter is the current accelerator pedal opening, and the power demand intensity is evaluated based on the current accelerator pedal opening.

5. The SOC optimization method according to claim 1, characterized in that, Also includes: If the difference between the endpoint SOC value and the lower limit threshold of SOC is greater than or equal to the first preset SOC threshold, then pure electric mode is used for driving.

6. The SOC optimization method according to claim 1, characterized in that, The second entry point is determined as follows: The second entry SOC value is calculated as follows: Second entry SOC value = (SOC value at start + SOC lower limit threshold) / 2; The second entry point is when the current SOC value reaches the second entry SOC value.

7. A SOC optimization system, characterized in that: Deployed in a vehicle, the system includes a memory (11) and a processor (12), the memory (11) for storing a computer program and the processor (12) for calling the computer program to execute the SOC optimization method as described in any one of claims 1 to 6.

8. A vehicle, characterized in that, Includes the SOC optimization system (1) as described in claim 7.

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