CN113320521B - Speed planning method and system for hybrid vehicle - Google Patents
Speed planning method and system for hybrid vehicle Download PDFInfo
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- B60W20/00—Control systems specially adapted for hybrid vehicles
- B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
- B60W20/15—Control strategies specially adapted for achieving a particular effect
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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- B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
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Abstract
The invention provides a speed planning method and system for a hybrid vehicle. Detecting a deceleration area in real time in the driving process, and acquiring a distance S between the hybrid vehicle and the deceleration area; calculating a sliding distance S according to the current speed of the hybrid vehicle and the predicted speed of the deceleration region 0 When S is 0 When the speed is more than or equal to S, reminding a driver to control the hybrid vehicle to slide; after the hybrid vehicle starts coasting, energy recovery is required to increase the deceleration since the hybrid vehicle cannot reach the deceleration region by pure coasting at this time. According to the method, an evaluation function is formulated according to an energy recovery maximization principle so as to calculate the optimal initial recovery time and the optimal motor torque sequence, the motor torque of the hybrid vehicle is controlled according to the optimal motor torque sequence, and energy recovery is started at the optimal initial recovery time, so that the driving performance and safety are ensured, the energy conversion loss is reduced, and the energy-saving and emission-reducing effects are improved.
Description
Technical Field
The invention relates to the technical field of new energy automobiles, in particular to a speed planning method and system for a hybrid vehicle.
Background
The hybrid vehicle is generally an oil-electric hybrid vehicle, that is, a vehicle driven by a mixture of fuel (gasoline, diesel oil) and electric energy. The hybrid automobile has high fuel economy and excellent running performance, the engine is driven by fuel, and the auxiliary drive of the motor is realized during starting and accelerating, so that the fuel consumption can be reduced, and the hybrid automobile has a wide development prospect.
The 48V hybrid automobile gradually becomes the mainstream in the hybrid automobile market due to the good energy-saving and emission-reducing performance and the lower cost. The 48V hybrid electric vehicle can effectively reduce energy consumption, on one hand, the energy conversion efficiency is improved through a reasonable energy distribution strategy, on the other hand, the hybrid electric vehicle can slide for as long as possible in the deceleration process, and the braking energy is recovered through the motor when necessary, so that the whole vehicle economy is improved.
Fig. 1 is a schematic structural diagram of a 48V hybrid vehicle. As shown in fig. 1, when the 48V hybrid vehicle is in pure coasting, the clutch is disengaged, and the engine and the 48V motor are disengaged from the power transmission chain, thereby reducing the drag loss during the coasting process and prolonging the coasting distance of the vehicle; when the vehicle slides and energy is recovered, the clutch is combined, the engine is cut off, the 48V motor recovers energy through appointed negative torque, and kinetic energy of the vehicle is converted into electric energy to be stored in the 48V power battery. However, because of the structural features of a hybrid vehicle, the engine is also towed during energy recovery, and therefore, there is a loss of engine towing power, and it is desirable to start energy recovery as late as possible in order to reduce this energy loss. However, the later the energy recovery, the slower the vehicle speed decreases, especially when the starting vehicle speed is high, requiring a longer braking distance to drop to a specified speed. Therefore, when the coasting distance is short and the current vehicle speed is high, how to set the time (initial recovery time) for starting energy recovery and the motor torque (recovered motor torque sequence) at each discrete time to reduce energy conversion loss and satisfy the braking requirement is a problem to be solved.
Disclosure of Invention
The invention aims to provide a speed planning method and a speed planning system for a hybrid vehicle, which can realize the maximization of energy recovery under the condition of meeting braking requirements by planning the initial recovery time and the motor torque sequence of the hybrid vehicle during sliding.
In order to achieve the above object, the present invention provides a speed planning method for a hybrid vehicle, comprising:
detecting a deceleration area in real time in the running process of the hybrid vehicle, and acquiring the distance s between the hybrid vehicle and the deceleration area;
calculating a theoretical sliding distance s according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 When s is 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
after the hybrid vehicle starts to slide, calculating an optimal initial recovery time and an optimal motor torque sequence according to an energy recovery maximization principle;
and controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence, and starting to recover energy at the optimal initial recovery moment.
Optionally, the theoretical sliding distance s is calculated according to the following formula 0 ：
Wherein v is 0 Is the current speed, v, of the hybrid vehicle s Is the predicted speed of the deceleration zone, m is the mass of the hybrid vehicle, μ is the rolling resistance coefficient, C D And the coefficient of air resistance is rho, the air density is rho, the frontal area is A, the road gradient is alpha, and v is the speed of the hybrid vehicle at each discrete moment.
Optionally, the optimal starting recovery time and the optimal motor torque sequence are calculated according to the energy recovery maximization and the total sliding time minimization principle.
Optionally, the step of calculating the optimal initial recovery time and the optimal motor torque sequence according to the energy recovery maximization and the total sliding time minimization principle includes:
making an evaluation function according to the energy recovery maximization and the total sliding time minimization principle, and making a constraint condition of the evaluation function;
setting an initial starting recovery time, obtaining a remaining distance between the hybrid vehicle and the deceleration area after the initial starting recovery time, dividing the remaining distance into n equal parts according to discrete distance intervals, and converting a calculation target of the evaluation function into a motor torque for determining each discrete distance interval, wherein n is greater than or equal to 1;
and solving an optimal solution of the evaluation function according to the constraint condition, wherein the optimal solution is the optimal motor recovery torque sequence at the optimal initial recovery moment.
Optionally, the evaluation function is:
wherein, T m As motor torque, ω m Is the motor speed, f (T) m ·ω m ) Mechanical work recovered for the motor within a discrete distance interval Δ s, t s Is the total time of coasting eta m Efficiency of charging of the motor, w 1 And w 2 Are all weight factors, s l To set the remaining glide distance at the initial recovery time.
Optionally, an ant colony optimization algorithm is used to solve the optimal solution of the evaluation function.
Optionally, the constraint condition is a range limit on the motor torque, a difference value of the motor torques at two adjacent discrete distances, and an actual sliding distance.
Optionally, maximum value of recovered energy E max Comprises the following steps:
wherein, J ICE_strt Energy consumption for starting the engine of the hybrid vehicle, t s For total coasting time, t strt For the optimal initial recovery moment, P drg Is the towing power of the engine of the hybrid vehicle.
Optionally, when s 0 When + delta is less than or equal to s, the hybrid vehicle drives to s 0 And + δ, wherein δ is the distance traveled by the hybrid vehicle within the driver's reaction time.
Optionally, the deceleration area is detected in real time by acquiring one or more of road condition information, indicator light information or navigation positioning information of the hybrid vehicle during driving.
The invention also provides a speed planning system of the hybrid vehicle, which comprises the following components:
a calculation module used for calculating the distance s between the hybrid vehicle and the deceleration area according to the deceleration area detected in real time in the driving process of the hybrid vehicle and calculating the sliding distance s according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 ；
A warning module for use in s 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
the speed planning module is used for activating the hybrid vehicle after the hybrid vehicle starts to slide, and making an evaluation function according to an energy recovery maximization principle so as to calculate the optimal initial recovery time and the optimal motor torque sequence;
and the execution module is used for controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence and starting to recover energy at the optimal initial recovery moment.
Optionally, the hybrid vehicle is a 48V hybrid vehicle.
In the speed planning method and the speed planning system of the hybrid vehicle, a deceleration area is detected in real time in the running process of the hybrid vehicle, and the distance S between the hybrid vehicle and the deceleration area is obtained; calculating a sliding distance S according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 When S is 0 When the speed is more than or equal to S, reminding a driver to control the hybrid vehicle to slide; after the hybrid vehicle starts coasting, energy recovery is required to increase the deceleration since the hybrid vehicle cannot reach the deceleration region by pure coasting at this time. The invention calculates the optimal initial recovery time and the optimal motor torque sequence according to the energy recovery maximization principle, controls the motor torque of the hybrid vehicle according to the optimal motor torque sequence, starts to recover energy at the optimal initial recovery time,therefore, on the premise of ensuring the driving performance and the safety, the energy-saving and emission-reducing effects of the vehicle are effectively improved, the energy conversion loss is reduced, and the utilization rate of fuel oil is further improved.
Drawings
FIG. 1 is a schematic structural diagram of a 48V hybrid vehicle;
FIG. 2 is a schematic diagram of a speed trajectory of a hybrid vehicle at four different initial recovery moments according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for speed planning of a hybrid vehicle according to an embodiment of the present invention;
fig. 4 is a flowchart of an ant colony optimization algorithm provided in the embodiment of the present invention;
fig. 5 is a block diagram of a speed planning system of a hybrid vehicle according to an embodiment of the present invention;
wherein the reference numerals are:
10-a calculation module; 20-an alert module; 30-a speed planning module; 40-executing the module.
Detailed Description
The following describes in more detail embodiments of the present invention with reference to the schematic drawings. The advantages and features of the present invention will become more apparent from the following description. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
Suppose that a hybrid vehicle detects a deceleration zone at a distance s from itself and the current speed of the hybrid vehicle is v 0 The predicted speed of the deceleration region is v s (wherein, v s May also be equal to 0), the hybrid vehicle may be calculated from v 0 Pure glide to v s Required sliding distance s 0 . Theoretically when s = s 0 In the meantime, the hybrid vehicle can just purely slide to the deceleration area, the kinetic energy of the hybrid vehicle is completely consumed by the road resistance work, no energy conversion loss exists theoretically, and the energy consumption is the lowest at the moment.
But due to the limited detection capability of the hybrid vehicle and the roadThe scene is complicated and changeable, and generally when the deceleration area is detected, s already appears 0 S, the hybrid vehicle cannot completely rely on road resistance to convert v within s 0 Down to v s At this time, the hybrid vehicle must be decelerated more quickly by the deceleration action of the energy recovered by the motor. s to s 0 The more small, the more recoverable the energy represents to the motor. Maximum value E of theoretically recovered energy of motor max Comprises the following steps:
wherein m is the mass of the hybrid vehicle, μ is the rolling resistance coefficient, α is the road grade, C D Is the air drag coefficient, ρ is the air density, A is the frontal area, J ICE_strt Energy consumption for starting an engine of the hybrid vehicle, t s For total coasting time, t strt For the optimal initial recovery moment, P drg V is the speed of the hybrid vehicle (which can be calculated from the deceleration superposition) at each discrete instant, which is the power drawn by the engine of the hybrid vehicle.
As is clear from the structural features of hybrid vehicles, the engine is also towed during the recovery of the motor torque, so the loss of the engine towing power must be considered, and in order to reduce this energy loss, it is desirable to start energy recovery as late as possible during coasting, however, the later the recovery, the slower the vehicle speed is reduced, and v may not be recovered within s 0 Down to v s And wind resistance power accumulated loss
Becomes large and a part of the energy is lost. FIG. 2 shows a schematic diagram of the speed trajectory of a hybrid vehicle at four different starting recovery moments, wherein the line l 1 For the initial recovery time t 1 Corresponding velocity trace, line l 2 For the initial recovery time t 2 Corresponding velocity trace, line l 3 For the initial recoveryAt time t 3 Corresponding velocity trace, line l 4 For the initial recovery time t 4 The corresponding velocity trajectory. As can be seen from fig. 2, the hybrid vehicle is coasting only until the initial recovery moment, at which stage the hybrid vehicle decelerates due to road resistance (in the case of uniform deceleration), without energy conversion losses; after starting energy recovery, the hybrid vehicle decelerates to the end vehicle speed according to the determined deceleration of the motor torque, the speed track of the hybrid vehicle is different at different starting recovery moments, the determined deceleration is different under different motor torque sequences, and the speed track of the hybrid vehicle is naturally different.
It will be appreciated that there may be many combinations of starting recovery moments and motor torque sequences, with the energy recovered being different in different combinations.
Based on this, as shown in fig. 3, the present embodiment provides a speed planning method for a hybrid vehicle, including:
step S1: detecting a deceleration area in real time in the running process of the hybrid vehicle, and acquiring the distance s between the hybrid vehicle and the deceleration area;
step S2: calculating a theoretical sliding distance s according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 When s is 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
and step S3: after the hybrid vehicle starts to slide, calculating an optimal initial recovery time and an optimal motor torque sequence according to an energy recovery maximization principle;
and step S4: and controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence, and starting to recover energy at the optimal initial recovery moment.
Specifically, step S1 is executed, and during the running process of the hybrid vehicle, the intelligent internet of things system mounted in the hybrid vehicle may obtain the road condition information (including the road condition information) in front of the hybrid vehicle in real time through channels such as a radar, a camera, or a mapCongestion, intersections, zebra crossings, etc.), indicator light information (traffic light color, remaining time, etc.) or navigation positioning information (slope, road shape, etc.). If it is determined from these information that there is an upcoming deceleration zone in front of the hybrid vehicle, for example, a congestion, an obstacle, or a speed limit zone in front is detected, the distance s between the hybrid vehicle and the deceleration zone and the current speed v of the hybrid vehicle may be obtained at this time 0 And a predicted speed v of the deceleration region s 。
Next, step S2 is executed to calculate the distance S between the hybrid vehicle and the deceleration area according to the following formula 0 ：
Wherein v is 0 Is the current speed, v, of the hybrid vehicle s Is the predicted speed of the deceleration zone, m is the mass of the hybrid vehicle, μ is the rolling resistance coefficient, C D And p is the air drag coefficient, p is the air density, a is the frontal area, α is the road gradient, and v is the speed of the hybrid vehicle at each discrete time.
Then, step S3 is executed, when S 0 When s, it indicates that the hybrid vehicle can purely slide to the deceleration zone without energy recovery. Considering that the driver has reaction time, when s 0 When + delta is less than or equal to s, the hybrid vehicle drives to s 0 And before + delta, reminding the driver of releasing an accelerator pedal and a brake pedal, and starting the hybrid vehicle to slide, wherein delta is the distance traveled by the hybrid vehicle in the reaction time of the driver. In this case, when the driver releases the accelerator pedal and the brake pedal, the hybrid vehicle is purely coasting to the deceleration region, and there is theoretically no energy conversion loss (chemical energy-kinetic energy-electrical energy conversion loss), and the energy consumption is the lowest.
When s is 0 When the speed is more than or equal to s, the hybrid vehicle cannot slide to the deceleration area purely, and the speed needs to be reducedIncreasing the deceleration to effect energy recovery (if it is considered that the driver has a reaction time, in fact when s 0 The hybrid vehicle also cannot purely coast to the deceleration region when + δ > s). At the moment, a driver is reminded to release an accelerator pedal and a brake pedal immediately, and after the driver releases the accelerator pedal and the brake pedal, an evaluation function is formulated according to the energy recovery maximization and total coasting time minimization principle, wherein the evaluation function is as follows:
wherein, T m As motor torque, ω m Is the motor speed, f (T) m ·ω m ) T is the mechanical work recovered by the motor within the discrete distance interval Δ s (the mechanical work recovered by the motor is negative, so the smaller the mechanical work recovered by the motor, the larger the energy recovered), t s Is total time of sliding, η m Efficiency of charging of the motor, w 1 And w 2 Are all weight factors (if the requirement on the sliding time is not high, w 2 May take on values close to zero), s l To set the remaining glide distance at the initial recovery time.
Next, constraints for the evaluation function are formulated, taking into account the motor torque T, the battery recovery capability and the braking safety limits m Needs to be within a set range, i.e. T min ≤T m ≤T max (ii) a Considering the influence of the drivability, the difference value Delta T of the motor torques under two adjacent discrete distances m Needs to be within a set range, i.e. Δ T m ≤ΔT lim (ii) a Actual sliding distance s of the hybrid vehicle coast Needs to be within a set range (to avoid the hybrid vehicle being unable to reach the deceleration zone or reaching the deceleration zone with a speed that is too far from the predicted speed), i.e., s-epsilon ≦ s coast S, wherein the maximum value and the minimum value of the motor torque, and the maximum value delta T of the difference value of the motor torque under two adjacent discrete distances lim And the margin distance epsilon can be obtained by calibrating or measuring a specific hybrid vehicle.
Then, an ant colony optimization algorithm can be adopted to solve an optimal solution of the evaluation function according to the constraint conditions, wherein the optimal solution is the optimal motor recovery torque sequence at the optimal initial recovery moment. Specifically, as shown in fig. 4, an initial recovery starting time t is set, and a remaining distance s between the hybrid vehicle and the deceleration area after the initial recovery starting time t can be obtained l And the speed v of the hybrid vehicle at the initial recovery moment t l . Will leave the sliding distance s l The discrete distance interval deltas is divided into n equal parts (less than one equal part is calculated as one equal part), the calculation method objective is converted into a motor torque that determines each of the discrete distance intervals deltas, and then the ant colony optimization algorithm can be started for optimization solution.
The ant colony optimization algorithm is a bionic algorithm for simulating foraging behavior of ant colony, each ant independently searches feasible solutions in a solution space, when the ants meet an intersection which does not pass through, one path is randomly selected to move forwards, pheromones related to the path length are released, the path length is in inverse proportion to the pheromone concentration, when other subsequent ants reach the intersection, the path with more pheromones is selected to move forwards with relatively high probability, and more pheromones are left on the path, so the ants move back and forth to form a positive feedback mechanism, as the algorithm advances, the pheromones on the optimal solution path are gradually increased, the passing ants are more and more, the pheromones on other paths are gradually faded, and finally all ants can select the path which passes through the optimal solution. The whole optimizing process is carried out through pheromone exchange, and finally the optimal path is obtained. The ant colony optimization algorithm comprises the following steps:
1) Initialization
Setting the ant number H, time t =0 and cycle number N c =0, maximum number of cycles N cmax . Randomly generating a set of network parameters I l Let the pheromone τ of the path (i, j) j (I i ) = C, initial time Δ τ j (I i ) =0, H ants are randomly placed on some H elements of a set of n (n is a discrete distance number).
2) Start all ants
Each ant spreads over all sets, and one is selected from m elements in each set according to the following rule, and finally the obtained n elements form a group of network parameters. The rules are as follows:
for set I l Ant k (k =1,2 \8230; \8230H) obtained the probability of selecting the jth element from the following formula. And the element with the maximum transition probability is selected, and the position j of the element is recorded in a taboo table.
3) The second step is repeated until H ants reach the food source, indicating that H sets of network parameters (one for each ant) were selected from the full set.
4) Let t = t + N, N c ＝N c +1, inputting the trajectory result obtained by the selected values of the H ants into the evaluation function, and then selecting the minimum value of the evaluation function in all the ants as the optimal solution. The pheromone is then re-updated as follows:
τ j (I l )(t+N)＝(1-ρ)τ j (I l )+Δτ j (I l )
wherein f is k Obtained by inputting the result of the kth ant into the evaluation function
5) If all ants converge to a path or cycle number N c ＞N cmax If not, outputting the optimal solution and ending the algorithmEmptying the sports table goes to the second step.
The output optimal solution is the optimal motor torque sequence under the current initial recovery moment, then the initial recovery moment t is changed, and the total time t from 0 to sliding is calculated in sequence s Then obtaining a group of optimal torque sequences in all initial recovery moments through an evaluation function, wherein the corresponding initial recovery moment is the optimal initial recovery moment t opt And then the optimal vehicle speed track is calculated.
For the hybrid vehicle, the ant colony optimization algorithm has a large calculation burden, and the problem can be alleviated by simplifying the algorithm, such as reducing the number of ants or the quantity of optional elements in each set, or improving the algorithm itself, such as for example, using the optimal position transfer mechanism of the particle swarm optimization algorithm or the cross variation operation of the genetic algorithm for reference, and accelerating the convergence speed; the method can also be used for preparing a table through off-line calculation, and the table look-up can be carried out during on-line application (under the condition that the parameters of the hybrid vehicle and the road working conditions are determined, the optimal initial recovery time and the optimal torque sequence can be obtained according to the table look-up of the initial speed and the sliding distance). Of course, the present invention is not limited to the use of the ant colony optimization algorithm to calculate the optimal initial recovery time and the optimal torque sequence, and other optimization algorithms may be used.
And finally, executing a step S4, controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence, and starting to recover energy at the optimal initial recovery moment, so that the energy conversion loss is reduced, and the energy recovery maximization is realized.
Based on this, the present embodiment further provides a speed planning system for a hybrid vehicle, including:
the hybrid vehicle speed control system comprises a calculation module 10, wherein an intelligent internet of things system carried on a hybrid vehicle detects a deceleration area and the predicted speed of the deceleration area in real time in the running process of the hybrid vehicle, and the calculation module 10 can calculate the distance s between the hybrid vehicle and the deceleration area according to the detection information of the intelligent internet of things system and calculate the current speed of the hybrid vehicle according to the current speed of the hybrid vehicleCalculating a coasting distance s from the velocity and the predicted velocity of the deceleration region 0 ；
An alert module 20 connected to the computing module 10 for alerting the user at s 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
the speed planning module 30 is activated after the hybrid vehicle starts to slide, and calculates the optimal initial recovery time and the optimal motor torque sequence according to the energy recovery maximization principle;
and the execution module 40 is used for controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence and starting to recover energy at the optimal initial recovery moment.
In the invention, the hybrid vehicle is not limited to a 48V hybrid vehicle, and can be other hybrid vehicles, hybrid ships, hybrid airplanes and the like.
In summary, in the speed planning method and system for a hybrid vehicle provided in the embodiments of the present invention, a deceleration area is detected in real time during a traveling process of the hybrid vehicle, and a distance S between the hybrid vehicle and the deceleration area is obtained; calculating a sliding distance S according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 When S is 0 When the speed is more than or equal to S, reminding a driver to control the hybrid vehicle to slide; after the hybrid vehicle starts to slide, because the hybrid vehicle cannot reach a deceleration area through pure sliding at the moment, energy recovery is needed to increase the deceleration.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention in any way. It will be understood by those skilled in the art that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (11)
1. A method of speed planning for a hybrid vehicle, comprising:
detecting a deceleration area in real time in the running process of the hybrid vehicle, and acquiring the distance s between the hybrid vehicle and the deceleration area;
calculating a theoretical sliding distance s according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 When s is 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
after the hybrid vehicle starts to slide, an evaluation function is formulated according to an energy recovery maximization principle so as to calculate an optimal initial recovery moment and an optimal motor torque sequence;
controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence, and starting to recover energy at the optimal initial recovery moment;
the evaluation function is:
wherein, T m As motor torque, ω m Is the motor speed, f (T) m ·ω m ) Mechanical work recovered for the motor within a discrete distance interval Δ s, t s Is total time of sliding, η m Efficiency of charging of the motor, w 1 And w 2 Are all weight factors, s l To set the remaining glide distance at the initial recovery time.
2. A method for speed planning of a hybrid vehicle according to claim 1, characterized in that the theoretical sliding distance is calculated according to the following formulaFrom s 0 ：
Wherein v is 0 Is the current speed, v, of the hybrid vehicle s Is the predicted speed of the deceleration zone, m is the mass of the hybrid vehicle, μ is the rolling resistance coefficient, C D And p is the air drag coefficient, p is the air density, a is the frontal area, α is the road gradient, and v is the speed of the hybrid vehicle at each discrete time.
3. A method for speed planning of a hybrid vehicle according to claim 1, characterized in that the optimal starting recovery moment and the optimal motor torque sequence are calculated according to the energy recovery maximization and the total coasting time minimization principles.
4. A method for speed planning of a hybrid vehicle according to claim 3 wherein the step of calculating the optimal initial recovery time and the optimal motor torque sequence based on the energy recovery maximization and the total coasting time minimization comprises:
an evaluation function is formulated according to the energy recovery maximization and the total sliding time minimization principle, and constraint conditions of the evaluation function are formulated;
setting an initial starting recovery time, obtaining a remaining distance between the hybrid vehicle and the deceleration area after the initial starting recovery time, dividing the remaining distance into n equal parts according to discrete distance intervals, and converting a calculation target of the evaluation function into a motor torque for determining each discrete distance interval, wherein n is greater than or equal to 1;
and solving an optimal solution of the evaluation function according to the constraint condition, wherein the optimal solution is an optimal motor recovery torque sequence at the optimal initial recovery moment.
5. A method for speed planning for a hybrid vehicle according to claim 1 or 4 wherein the optimal solution for the merit function is solved using an ant colony optimization algorithm.
6. A method for speed planning for a hybrid vehicle according to claim 1 or 4 wherein the constraints are range limits for motor torque, difference between motor torques at two adjacent discrete distances, and actual distance travelled.
7. Method for speed planning of a hybrid vehicle according to claim 2, characterized in that the maximum value E of the recovered energy is max Comprises the following steps:
wherein, J ICE_strt Energy consumption for starting an engine of the hybrid vehicle, t s Total time of coasting, t strt For the optimal initial recovery moment, P drg Is the towing power of the engine of the hybrid vehicle.
8. Method for speed planning of a hybrid vehicle according to claim 1, characterized in that when s is 0 When + delta is less than or equal to s, the hybrid vehicle drives to s 0 And before + delta, reminding a driver to control the hybrid vehicle to slide, wherein delta is the distance traveled by the hybrid vehicle in the reaction time of the driver.
9. The method for speed planning of a hybrid vehicle according to claim 1, wherein the deceleration zone is detected in real time by obtaining one or more of road condition information, indicator light information or navigation positioning information of the hybrid vehicle during driving.
10. A speed planning system for a hybrid vehicle, comprising:
calculating outA module for calculating a distance s between the hybrid vehicle and the deceleration area according to the deceleration area detected in real time during the traveling of the hybrid vehicle, and calculating a sliding distance s according to the current speed of the hybrid vehicle and the predicted speed of the deceleration area 0 ；
A warning module for use in s 0 Reminding a driver to control the hybrid vehicle to slide when the speed is more than or equal to s;
the speed planning module is used for activating the hybrid vehicle after the hybrid vehicle starts to slide, and making an evaluation function according to an energy recovery maximization principle so as to calculate the optimal initial recovery time and the optimal motor torque sequence;
the execution module is used for controlling the motor torque of the hybrid vehicle according to the optimal motor torque sequence and starting to recover energy at the optimal initial recovery moment;
the merit function is:
wherein, T m As motor torque, ω m Is the motor speed, f (T) m ·ω m ) Mechanical work recovered for the motor within a discrete distance interval Δ s, t s Is the total time of coasting eta m Efficiency of charging of the motor, w 1 And w 2 Are all weight factors, s l To set the remaining glide distance at the initial recovery time.
11. The hybrid vehicle speed planning system of claim 10 wherein the hybrid vehicle is a 48V hybrid vehicle.
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