Oil-saving control method for predictive cruise based on map

Abstract

The invention discloses a map-based predictive cruise oil-saving control method, which comprises the following steps of: firstly, acquiring slope information of a front road based on an offline map, dividing road condition types according to the slope information, and then dividing the whole course into a plurality of road sections at fixed intervals; secondly, for each road section, calculating vehicle driving energy including driving force, kinetic energy change and resistance consumption; thirdly, a comprehensive cost function with the lowest oil consumption and the stable vehicle speed as targets is constructed, and the optimal target vehicle speed of each road section is solved with the principle of total cost minimization; and finally, the power consumption of each section is calculated based on the optimal vehicle speed, the energy distribution of an engine and a motor is prospectively and cooperatively planned, and the state of charge (SOC) of a battery is dynamically adjusted to be maintained in a high-efficiency interval (such as 0.2-0.95), so that the optimization of the global energy consumption is realized. The fuel consumption of the vehicle can be remarkably reduced, the endurance mileage is increased, and important economical efficiency and environmental protection value are achieved.

Description

Technical Field

[0001] This invention relates to the technical field of vehicle energy-saving control, and in particular to a map-based predictive cruise fuel-saving control method. Background Technology

[0002] With the global energy crisis and environmental pollution becoming increasingly severe, energy-saving and emission-reduction technologies in the automotive industry have become a key research focus. For vehicles with multiple energy sources, such as hybrid electric vehicles and range-extended electric vehicles, efficient energy management is crucial for achieving low fuel consumption and long driving range. Traditional vehicle energy management strategies, such as cruise control, primarily rely on feedback control based on current instantaneous speed or simple road conditions, lacking effective utilization of road information ahead and exhibiting problems such as control lag and poor adaptability to complex road conditions.

[0003] Existing predictive cruise control technologies rely to some extent on GPS or map data to obtain information about the slope ahead and adjust vehicle speed accordingly. However, these methods often have the following limitations:

[0004] First, the road classification is too coarse and fails to identify road condition types in a refined manner based on continuous slope change characteristics (such as continuous uphill, uphill followed by downhill, etc.), resulting in insufficient predictability and pertinence of the control strategy.

[0005] Second, the energy calculation model is not accurate enough and fails to calculate the comprehensive energy consumption, including kinetic energy change, rolling resistance, air resistance and slope resistance, in segments with a sufficiently high resolution (e.g. every 25 meters), which causes the optimization results to deviate from the actual energy consumption.

[0006] Third, the optimization goals are relatively singular, usually focusing only on the lowest fuel consumption, without taking vehicle speed stability as an important cost constraint for comprehensive consideration. This can easily lead to frequent acceleration and deceleration of the vehicle, affecting driving comfort, and the actual fuel-saving effect may not be optimal.

[0007] Fourth, for hybrid systems, the dynamic planning of road conditions ahead and battery state of charge (SOC) is not tightly coupled, making it impossible to intelligently plan the use of fuel and electricity during long-distance driving. It is difficult to maintain battery energy in an efficient range throughout the entire journey, thus failing to achieve optimal utilization of global energy.

[0008] Therefore, there is an urgent need in this field for a fuel-saving method that can deeply integrate high-precision map information, perform refined road segmentation and energy modeling, and achieve global optimization control under multiple objective constraints (such as minimum fuel consumption, stable vehicle speed, and battery SOC maintenance) to overcome the above-mentioned defects of the existing technology. Summary of the Invention

[0009] The technical problem to be solved by this invention is: in order to solve the problems existing in the above-mentioned background technology, a map-based predictive cruise fuel-saving control method is provided. By introducing the slope information ahead through offline maps, the method performs path minimum energy planning and power consumption change calculation, thereby optimizing the energy consumption of the engine, realizing vehicle fuel-saving control, reducing operating costs, and effectively protecting the environment.

[0010] The technical solution adopted by this invention to solve its technical problem is: a map-based predictive cruise fuel-saving control method, comprising the following steps:

[0011] Step 1: Divide the road into several road condition types; Based on the distance and corresponding slope information within 30km ahead sent by the vehicle's offline map, determine the road condition type of the road within 30km ahead.

[0012] Step 2: Based on the road condition type determined in Step 1, divide the entire route into multiple dry sections at 100m intervals;

[0013] Step 3: For each segment divided in Step 2, calculate the energy consumed by the vehicle's driving. The calculation formula is as follows:

[0014] + (1)

[0015] The meanings of the symbols in formula (1) are as follows:

[0016] Indicates the driving force at the wheel ends of the vehicle;

[0017] Indicates the distance of each segment;

[0018] This represents the change in kinetic energy.

[0019] This represents the energy consumed by vehicle resistance;

[0020] The calculation formula is:

[0021] (2)

[0022] The meanings of the symbols in formula (2) are as follows:

[0023] This represents the final velocity for each distance segment;

[0024] This represents the initial velocity for each distance segment;

[0025] The calculation formula is:

[0026] (3)

[0027] The meanings of the symbols in formula (3) are as follows:

[0028] Indicates the total mass of the vehicle;

[0029] Indicates the coefficient of road friction;

[0030] Indicates the slope angle of each segment;

[0031] Indicates the air drag coefficient;

[0032] Indicates air density;

[0033] Indicates the windward area;

[0034] Represents gravitational acceleration;

[0035] Step 4: Conduct a cost assessment based on Step 3, taking into account two constraints.

[0036] Step 5: Total cost calculated based on Step 3 The optimal vehicle speed for each segment is determined with the goal of minimizing total cost, thereby determining the optimal energy consumption.

[0037] Step 6: For each segment divided in Step 2, calculate the vehicle's battery consumption. ;

[0038] Step 7: For each segment divided in Step 2, combine the total energy consumption and electrical power consumption of each segment obtained in Steps 3 and 6 to calculate the energy consumed by the engine. The formula is:

[0039] (4)

[0040] In formula (4), each symbol represents the following meaning:

[0041] Indicates the vehicle's battery power consumption;

[0042] This indicates the energy consumed by the engine.

[0043] To further explain, in the above technical solution, the first step includes one of the following road condition types: continuous uphill, continuous downhill, uphill followed by downhill, downhill followed by uphill, and flat road.

[0044] To further explain, in the above technical solution, the cost assessment method in step 4 includes the following steps:

[0045] Step 41: Aiming to minimize the driving and braking forces at the vehicle's wheel ends, unnecessary acceleration and deceleration are avoided to reduce fuel consumption. The formula for calculating cost 1 is:

[0046] (5)

[0047] The meanings of each expression in formula (5) are as follows:

[0048] This represents cost 1, which is the cost based on minimizing fuel consumption.

[0049] This indicates the driving force at the vehicle's wheel ends for each segment;

[0050] Step 42, with the goal of approaching the set speed and reducing speed fluctuations, the formula for calculating cost 2 is as follows:

[0051] (6)

[0052] The meanings of each expression in formula (6) are as follows:

[0053] This represents cost 2, which is the cost based on the optimal stable vehicle speed.

[0054] Indicates the target vehicle speed;

[0055] Step 43: Calculate the total cost. The formula for calculating the total cost is:

[0056] (7)

[0057] The meanings of the symbols in formula (7) are as follows:

[0058] This represents the total cost, which is the weighted sum of cost 1 and cost 2.

[0059] This indicates a weighting coefficient of 1;

[0060] This indicates a weighting factor of 2;

[0061] Indicates the first Change in kinetic energy of segment;

[0062] Indicates the first Change in kinetic energy of segment.

[0063] To further explain, in the above technical solution, the vehicle's battery power consumed in step 6... Calculate as follows:

[0064] Step 61: Start acquiring input data, including current vehicle speed, current SOC, and information on 301 gradient points;

[0065] Step 62: Calculate the slope data;

[0066] Step 63: Calculate the maximum speed limit for the corresponding road segment based on the slope.

[0067] Step 64: Adjust the reference speed according to the slope;

[0068] Step 65: Calculate the required power at various locations along the future road segment, including rolling resistance, air resistance, and gradient resistance; based on the relationship between the required power and the engine's maximum power, handle four cases:

[0069] When the demand power > 0 and is greater than the engine's maximum power, the motor assists in driving, calculates the power difference of the road segment, and converts the driving power and electrical accessory power together into the discharge amount (kWh), which is then further converted into the SOC difference.

[0070] When the required power is greater than 0 but not greater than the engine's maximum power, the vehicle is driven on pure gasoline. In this section, the motor does not need to be charged or discharged. Only the discharge amount of the electrical accessories is calculated and further converted into the SOC difference.

[0071] When the demand power is ≤0 and greater than the maximum negative power of the motor, regenerative braking is performed. When the absolute value of the demand power is not greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the discharge amount of the road section and further converted into the SOC difference. When the absolute value of the demand power is greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the charging amount of the road section and further converted into the SOC difference.

[0072] When the required power is ≤0 and not greater than the maximum negative power of the motor, the charging amount of the road section is calculated based on the maximum negative power of the motor and the power of the electrical accessories, and then further converted into the SOC difference.

[0073] The SOC difference of the next road segment is accumulated and the limit SOC is calculated in order of distance from the current position of the vehicle to 30km.

[0074] Under various circumstances, if the SOC limit of the next segment is within the range of 0.2 to 0.95, a recalculation is performed; if it exceeds this range, corresponding charging and discharging adjustments are made; if all segments are within the range, the charge is maintained, and the predicted SOC value for the next moment is finally output.

[0075] The beneficial effects of this invention are as follows: By integrating high-precision map information with multi-objective optimization algorithms, globally optimal management of vehicle energy consumption is achieved. Specifically, firstly, by refining the classification and segmentation of the road ahead and combining it with a comprehensive energy consumption model, the accuracy of energy demand prediction is significantly improved; secondly, by introducing a multi-objective cost function centered on minimizing fuel consumption and maintaining stable vehicle speed, unnecessary acceleration and deceleration are effectively avoided, further reducing energy consumption while ensuring driving smoothness; finally, by proactively and collaboratively planning road segment energy consumption and battery SOC, the fuel-electric energy allocation strategy is intelligently optimized, ensuring that the battery remains in a high-efficiency range throughout the entire journey. This invention ultimately achieves significant fuel savings, effectively reducing vehicle operating costs and emissions, and has significant environmental and economic value. Attached Figure Description

[0076] 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 some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0077] Figure 1 This is a schematic diagram illustrating the determination of the optimal energy consumption and optimal vehicle speed for each segment in step 5 of this invention.

[0078] Figure 2 This refers to the vehicle's electricity consumption calculated in step 6 of this invention. A schematic diagram of the calculation process. Detailed Implementation

[0079] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0080] See Figure 1 In this context, ost n represents cost n, All-cost represents total cost, and K represents the distance of the Kth segment.

[0081] See Figure 1 and 2 The diagram illustrates a map-based predictive cruise fuel-saving control method, which includes the following steps:

[0082] Step 1: Divide the road into several road condition types; Based on the distance and corresponding slope information within 30km ahead sent by the vehicle's offline map, determine the road condition type of the road within 30km ahead.

[0083] Step 2: Based on the road condition type determined in Step 1, divide the entire route into multiple dry sections at 100m intervals;

[0084] Step 3: For each segment divided in Step 2, calculate the energy consumed by the vehicle's driving. The calculation formula is as follows:

[0085] + (1)

[0086] The meanings of the symbols in formula (1) are as follows:

[0087] Indicates the driving force at the wheel ends of the vehicle;

[0088] Indicates the distance of each segment;

[0089] This represents the change in kinetic energy.

[0090] This represents the energy consumed by vehicle resistance;

[0091] The calculation formula is:

[0092] (2)

[0093] The meanings of the symbols in formula (2) are as follows:

[0094] This represents the final velocity for each distance segment;

[0095] This represents the initial velocity for each distance segment;

[0096] The calculation formula is:

[0097] (3)

[0098] The meanings of the symbols in formula (3) are as follows:

[0099] Indicates the total mass of the vehicle;

[0100] Indicates the coefficient of road friction;

[0101] Indicates the slope angle of each segment;

[0102] Indicates the air drag coefficient;

[0103] Indicates air density;

[0104] Indicates the windward area;

[0105] Represents gravitational acceleration;

[0106] Step 4: Conduct a cost assessment based on Step 3, taking into account two constraints.

[0107] Step 5: Total cost calculated based on Step 3 The optimal vehicle speed for each segment is determined with the goal of minimizing total cost, thereby determining the optimal energy consumption.

[0108] Step 6: For each segment divided in Step 2, calculate the vehicle's battery consumption. ;

[0109] Step 7: For each segment divided in Step 2, combine the total energy consumption and electrical power consumption of each segment obtained in Steps 3 and 6 to calculate the energy consumed by the engine. The formula is:

[0110] (4)

[0111] In formula (4), each symbol represents the following meaning:

[0112] Indicates the vehicle's battery power consumption;

[0113] This indicates the energy consumed by the engine.

[0114] In step 1, several road condition types include one of the following: continuous uphill, continuous downhill, uphill followed by downhill, downhill followed by uphill, and flat road.

[0115] In step 4, the cost assessment method includes the following steps:

[0116] Step 41: Aiming to minimize the driving and braking forces at the vehicle's wheel ends, unnecessary acceleration and deceleration are avoided to reduce fuel consumption. The formula for calculating cost 1 is:

[0117] (5)

[0118] The meanings of each expression in formula (5) are as follows:

[0119] This represents cost 1, which is the cost based on minimizing fuel consumption.

[0120] This indicates the driving force at the vehicle's wheel ends for each segment;

[0121] Step 42, with the goal of approaching the set speed and reducing speed fluctuations, the formula for calculating cost 2 is as follows:

[0122] (6)

[0123] The meanings of each expression in formula (6) are as follows:

[0124] This represents cost 2, which is the cost based on the optimal stable vehicle speed.

[0125] Indicates the target (set) vehicle speed;

[0126] Step 43: Calculate the total cost. The formula for calculating the total cost is:

[0127] (7)

[0128] The meanings of the symbols in formula (7) are as follows:

[0129] This represents the total cost, which is the weighted sum of cost 1 and cost 2.

[0130] This indicates a weighting coefficient of 1;

[0131] This indicates a weighting factor of 2;

[0132] Indicates the first Change in kinetic energy of segment;

[0133] Indicates the first Change in kinetic energy of segment.

[0134] In step 6, the vehicle's battery power is consumed. Calculate as follows:

[0135] Step 61: Start acquiring input data, including current vehicle speed, current SOC, and information on 301 gradient points;

[0136] Step 62: Calculate the slope data;

[0137] Step 63: Calculate the maximum speed limit for the corresponding road segment based on the slope.

[0138] Step 64: Adjust the reference speed according to the slope;

[0139] Step 65: Calculate the required power at various locations along the future road segment, including rolling resistance, air resistance, and gradient resistance; based on the relationship between the required power and the engine's maximum power, handle four cases:

[0140] When the demand power > 0 and is greater than the engine's maximum power, the motor assists in driving, calculates the power difference of the road segment, and converts the driving power and electrical accessory power together into the discharge amount (kWh), which is then further converted into the SOC difference.

[0141] When the required power is greater than 0 but not greater than the engine's maximum power, the vehicle is driven on pure gasoline. In this section, the motor does not need to be charged or discharged. Only the discharge amount of the electrical accessories is calculated and further converted into the SOC difference.

[0142] When the demand power is ≤0 and greater than the maximum negative power of the motor, regenerative braking is performed. When the absolute value of the demand power is not greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the discharge amount of the road section and further converted into the SOC difference. When the absolute value of the demand power is greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the charging amount of the road section and further converted into the SOC difference.

[0143] When the required power is ≤0 and not greater than the maximum negative power of the motor, the charging amount of the road section is calculated based on the maximum negative power of the motor and the power of the electrical accessories, and then further converted into the SOC difference.

[0144] The SOC difference of the next road segment is accumulated and the limit SOC is calculated in order of distance from the current position of the vehicle to 30km.

[0145] Under various circumstances, if the SOC limit of the next segment is within the range of 0.2 to 0.95, a recalculation is performed; if it exceeds this range, corresponding charging and discharging adjustments are made; if all segments are within the range, the charge is maintained, and the predicted SOC value for the next moment is finally output.

[0146] The specific details are as follows:

[0147] 1. When the required power > 0 and the required power is greater than the engine's maximum power:

[0148] The system enters motor-assisted drive mode.

[0149] 1. Calculate the power difference (demand power - engine maximum power), and convert this power difference and the power of electrical accessories together into the battery discharge capacity (in kWh).

[0150] 2. Convert the discharge amount into SOC difference. The calculation formula is: SOC difference = Change in charge / Total battery charge; (Here, the charge decreases, and the SOC difference is negative)

[0151] II. When the required power > 0 and the required power ≤ the engine's maximum power:

[0152] When the system enters pure gasoline driving mode, the motor does not need to charge or discharge. It only calculates the battery discharge amount based on the accessory power and converts it into the SOC difference. The calculation formula is: SOC difference = change in charge / total battery charge (here the charge decreases, and the SOC difference is negative).

[0153] III. When the required power ≤ 0 and the required power > the maximum negative power of the motor:

[0154] The system enters regenerative braking mode.

[0155] 1. When the absolute value of the required power is less than the power of the electrical accessories, the discharge amount is calculated based on the required power and the power of the electrical accessories, and this discharge amount is converted into the SOC difference. The calculation formula is: SOC difference = change in charge / total battery charge (here the charge decreases, and the SOC difference is negative).

[0156] 2. When the absolute value of the required power is greater than or equal to the power of the electrical accessories, the charging amount is calculated based on the required power and the power of the electrical accessories, and this charging amount is converted into the SOC difference. The calculation formula is: SOC difference = change in charge / total battery charge (here the charge increases, and the SOC difference is positive).

[0157] IV. When the required power ≤ 0 and the absolute value of the required power ≤ the absolute value of the motor's maximum negative power:

[0158] The system enters the regenerative braking mode, calculates the charging amount based on the maximum negative power of the motor and the power of the electrical accessories, and converts this charging amount into the SOC difference. The calculation formula is: SOC difference = change in charge / total battery charge (here the charge increases, and the SOC difference is positive).

[0159] V. Predicting the ultimate SOC value of future road segments: Using the current SOC as the initial value and the current position of the vehicle as the starting point, the ultimate SOC of future road segments is calculated by accumulating the SOC differences of the above road segments in order of distance.

[0160] 1. The next road segment's maximum SOC = the current road segment's SOC + the SOC difference (since the SOC difference is negative for discharge and positive for charging, it should be the current road segment's SOC plus the SOC difference).

[0161] 2. Make judgments and adjustments based on the predicted limit SOC value:

[0162] If the limit SOC of the next road segment is between 0.2 and 0.95, and the next road segment is not the last road segment of 30km, then the limit SOC of the next road segment is used as the initial value to continue to calculate the limit SOC of the next road segment.

[0163] If the limit SOC of the next segment is not between 0.2 and 0.95, and the limit value is > 0.95, then discharge adjustment is performed: SOC at the next moment = current SOC - (limit SOC - 0.95), and this predicted value is output;

[0164] If the limit SOC of the next segment is not between 0.2 and 0.95, and the limit value is < 0.2, then charge adjustment is performed: SOC at the next moment = current SOC + (0.2 - limit SOC), and this predicted value is output;

[0165] If the SOC limit for the next segment is between 0.2 and 0.95, and the next segment is the last 30km segment, then maintain the battery level, set the SOC to 0.45, and output this predicted value.

[0166] The map-based predictive cruise fuel-saving control method of the present invention has the following beneficial effects:

[0167] More accurate prediction: By dividing the road ahead into specific types such as continuous uphill and downhill sections and segmenting them with a high resolution of 100 meters, energy planning is more in line with actual road conditions, greatly improving the foresight and accuracy of energy consumption prediction.

[0168] More optimized and smoother control: The system employs a dual cost function that integrates minimizing driving force (fuel saving) and minimizing vehicle speed deviation (smoothness) to reduce fuel consumption while effectively suppressing vehicle speed fluctuations, improving driving comfort, and avoiding energy waste caused by frequent acceleration or braking.

[0169] Smarter and more comprehensive energy management: By incorporating battery consumption (Batt) into the overall energy calculation, it enables forward-looking intelligent switching between engine and motor operating modes (such as assisted drive, pure fuel driving, and regenerative braking), and can dynamically adjust the battery SOC to keep it in the high-efficiency range of 0.2-0.95 for a long time, thereby achieving optimal global energy consumption throughout the entire process and significantly saving fuel.

[0170] More comprehensive benefits: Ultimately, the synergistic effect of the above technologies achieves a comprehensive benefit of reducing fuel consumption, operating costs, and exhaust emissions.

[0171] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A map-based predictive cruise fuel-saving control method, characterized in that, Includes the following steps: Step 1: Divide the road into several road condition types; Based on the distance and corresponding slope information within 30km ahead sent by the vehicle's offline map, determine the road condition type of the road within 30km ahead. Step 2: Based on the road condition type determined in Step 1, divide the entire route into multiple dry sections at 100m intervals; Step 3: For each segment divided in Step 2, calculate the energy consumed by the vehicle's driving. The calculation formula is: + （1） The meanings of the symbols in formula (1) are as follows: Indicates the driving force at the wheel ends of the vehicle; Indicates the distance of each segment; This represents the change in kinetic energy. This represents the energy consumed by vehicle resistance; The calculation formula is: （2） The meanings of the symbols in formula (2) are as follows: This represents the final velocity for each distance segment; This represents the initial velocity for each distance segment; The calculation formula is: （3） The meanings of the symbols in formula (3) are as follows: Indicates the total mass of the vehicle; Indicates the coefficient of road friction; Indicates the slope angle of each segment; Indicates the air drag coefficient; Indicates air density; Indicates the windward area; Represents gravitational acceleration; Step 4: Conduct a cost assessment based on Step 3, taking into account two constraints. Step 5: Total cost calculated based on Step 3 The optimal vehicle speed for each segment is determined with the goal of minimizing total cost, thereby determining the optimal energy consumption. Step 6: For each segment divided in Step 2, calculate the vehicle's battery consumption. ; Step 7: For each segment divided in Step 2, combine the total energy consumption and electrical power consumption of each segment obtained in Steps 3 and 6 to calculate the energy consumed by the engine. The formula is: （4） In formula (4), each symbol represents the following meaning: Indicates the vehicle's battery power consumption; This indicates the energy consumed by the engine.

2. The map-based predictive cruise fuel-saving control method according to claim 1, characterized in that: In the first step, the road condition types include one of the following: continuous uphill, continuous downhill, uphill followed by downhill, downhill followed by uphill, and flat road.

3. The map-based predictive cruise fuel-saving control method according to claim 1, characterized in that: In step 4, the cost assessment method includes the following steps: Step 41: Aiming to minimize the driving and braking forces at the vehicle's wheel ends, unnecessary acceleration and deceleration are avoided to reduce fuel consumption. The formula for calculating cost 1 is: （5） The meanings of each expression in formula (5) are as follows: This represents cost 1, which is the cost based on minimizing fuel consumption. This indicates the driving force at the vehicle's wheel ends for each segment; Step 42, with the goal of approaching the set speed and reducing speed fluctuations, the formula for calculating cost 2 is as follows: （6） The meanings of each expression in formula (6) are as follows: This represents cost 2, which is the cost based on the optimal stable vehicle speed. Indicates the target vehicle speed; Step 43: Calculate the total cost. The formula for calculating the total cost is: （7） The meanings of the symbols in formula (7) are as follows: This represents the total cost, which is the weighted sum of cost 1 and cost 2. This indicates a weighting coefficient of 1; This indicates a weighting factor of 2; Indicates the first Change in kinetic energy of segment; Indicates the first Change in kinetic energy of segment.

4. The map-based predictive cruise fuel-saving control method according to claim 1, characterized in that: In step 6, the vehicle's battery power is consumed. Calculate as follows: Step 61: Start acquiring input data, including current vehicle speed, current SOC, and information on 301 gradient points; Step 62: Calculate the slope data; Step 63: Calculate the maximum speed limit for the corresponding road segment based on the slope. Step 64: Adjust the reference speed according to the slope; Step 65: Calculate the required power at various locations along the future road segment, including rolling resistance, air resistance, and gradient resistance; based on the relationship between the required power and the engine's maximum power, handle four cases: When the demand power > 0 and is greater than the engine's maximum power, the motor assists in driving, calculates the power difference of the road segment, and converts the driving power and electrical accessory power together into the discharge amount (kWh), which is then further converted into the SOC difference. When the required power is greater than 0 but not greater than the engine's maximum power, the vehicle is driven on pure gasoline. In this section, the motor does not need to be charged or discharged. Only the discharge amount of the electrical accessories is calculated and further converted into the SOC difference. When the demand power is ≤0 and greater than the maximum negative power of the motor, regenerative braking is performed. When the absolute value of the demand power is not greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the discharge amount of the road section and further converted into the SOC difference. When the absolute value of the demand power is greater than the power of the electrical accessories, the demand power and the power of the electrical accessories are used together to calculate the charging amount of the road section and further converted into the SOC difference. When the required power is ≤0 and not greater than the maximum negative power of the motor, the charging amount of the road section is calculated based on the maximum negative power of the motor and the power of the electrical accessories, and then further converted into the SOC difference. The SOC difference of the next road segment is accumulated and the limit SOC is calculated in order of distance from the current position of the vehicle to 30km. In all cases, if the limit SOC of the next road segment is in the range of 0.2 to 0.95, then a recalculation is performed; If it exceeds this range, adjust the charging and discharging accordingly; If all road segments are within the range, maintain the power supply and finally output the predicted SOC value for the next time step.

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