CN117901840B - Hybrid power system energy management strategy targeting comprehensive efficiency optimization - Google Patents
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Abstract
The invention discloses a hybrid power system energy management strategy targeting the optimal comprehensive efficiency, comprising the following steps: determining a power unit, an energy storage unit and an electromechanical liquid coupling unit which are divided in advance in a hybrid power system, and determining target required power required to be output by the hybrid power system; distributing target demand power based on the output power of the power unit under the condition of optimal efficiency based on a preset distribution algorithm, and controlling the output of the power unit according to a distribution result; regulating and controlling the busbar voltage by adopting a PI algorithm, and distributing high-frequency power to the super capacitor and low-frequency power to the power battery by adopting a strategy of frequency domain distribution; the variable pump and the quantitative motor hydraulic system are adopted, and the output rotating speed of the quantitative motor is controlled on the basis of ensuring the normal output of the torque by adjusting the displacement of the variable pump. According to the invention, the output forms of different energy combinations can be controlled according to the required power, so that the overall efficiency of the hybrid power system is improved.
Description
Technical Field
The invention belongs to the field of hybrid power system energy management, and particularly relates to a hybrid power system energy management strategy aiming at optimizing comprehensive efficiency.
Background
The hybrid power is a new energy vehicle technology different from the traditional vehicle, and generally refers to oil and electricity hybrid power, namely, the vehicle is matched with a motor to provide auxiliary power on the basis of keeping the traditional internal combustion engine, the system can be flexibly regulated and controlled according to the actual running condition requirement of the whole vehicle, so that the engine is always kept in a working area with the best comprehensive performance, and the oil consumption and emission of the engine can be effectively reduced.
The existing hybrid power system has more energy storage units and only carries power batteries, so that high-frequency power generated in the running process of the system is not well utilized, and the waste of power performance is caused; the power unit module in the hybrid power system does not perform energy management for each engine working characteristic, and the optimal efficiency of the power unit module cannot be realized; the energy output form of the hybrid power system is single, and different energy output forms cannot be realized according to different working conditions, so that the overall efficiency of the hybrid power system is reduced.
Disclosure of Invention
In view of the above, the present invention aims to provide an energy management strategy of a hybrid power system, which aims at optimizing the comprehensive efficiency, and can control the output forms of different energy combinations according to the required power, so as to improve the overall efficiency of the hybrid power system.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the invention provides a hybrid power system energy management strategy aiming at optimizing comprehensive efficiency, which comprises the following steps:
Determining a power unit, an energy storage unit and an electromechanical liquid coupling unit which are divided in advance in a hybrid power system, and determining target required power required to be output by the hybrid power system;
For the power unit, distributing target required power based on the output power of the power unit under the condition of optimal efficiency based on a preset distribution algorithm, and controlling the output of the power unit according to a distribution result;
For the energy storage unit, regulating and controlling the busbar voltage by adopting a PI algorithm, and distributing high-frequency power to the super capacitor and low-frequency power to the power battery by adopting a strategy of frequency domain distribution;
for the electromechanical liquid coupling unit, a variable pump and a quantitative motor hydraulic system are adopted, and the output rotating speed of the quantitative motor is controlled on the basis of ensuring the normal output of the torque by adjusting the displacement of the variable pump.
Preferably, the preset allocation algorithm includes:
Dividing the target required power by the optimal output power of the power unit under the optimal efficiency condition to obtain a first multiple value and a first residual value, and taking the first multiple value and the first residual value as a first type of calculation result;
adding one to the first multiple value to obtain a second multiple value, subtracting the first residual value from the optimal output power to obtain a second residual value, and obtaining a second class calculation result according to the second multiple value and the second residual value;
determining a low-power distribution strategy according to the first type of calculation result, and calculating the first total efficiency of the power system under the low-power distribution strategy;
determining a high-power distribution strategy according to the second class of calculation results, and calculating the second total efficiency of the power system under the high-power distribution strategy;
comparing the first total efficiency with the second total efficiency, and determining the allocation strategy with the highest total efficiency as an allocation result.
Preferably, controlling the output of the power unit according to the distribution result includes:
Determining a high/low power allocation strategy corresponding to the allocation result, and determining a corresponding calculation result based on the high/low power allocation strategy;
determining a corresponding multiple value according to the calculation result, and selecting a corresponding number of power units according to the multiple value to perform output control according to the optimal output power;
And determining the corresponding residual value according to the calculation result, when the distribution result corresponds to the high-power distribution strategy, distributing the power corresponding to the residual value output by the power battery to the power battery for charging the power battery, and when the distribution result corresponds to the low-power distribution strategy, outputting the power corresponding to the residual value by the power battery for output power supplement.
Preferably, the preset allocation algorithm further comprises:
Collecting test data of a power unit, generating an MAP image, selecting an optimal efficiency point according to the MAP image, and obtaining a relation curve according to the optimal efficiency-power point;
Solving an optimal working point according to the relation curve, and maximally distributing the target required power to a power value corresponding to the optimal working point based on a preset sub-unit algorithm according to the optimal working point of the power unit;
and for the unallocated residual power in the required power, carrying out allocation and optimization on the residual power through a preset optimization algorithm, and finally selecting an optimal allocation scheme through multiple rounds of iteration to carry out power control and energy output on the power unit.
Preferably, the energy storage unit consists of a power battery with high energy density and a super capacitor with high power density;
regulating and controlling the bus voltage by adopting a PI algorithm, and controlling the balance of the bus voltage;
the method comprises the steps of carrying out high-frequency and low-frequency power distribution on target required power of a power system by adopting a strategy of frequency domain distribution, distributing high-frequency power to a super capacitor for bearing, and distributing low-frequency power to a power battery and a power unit for bearing together;
the energy storage unit outputs energy outwards when the allocated power is positive, and receives the external energy and enters a charging state when the allocated power is negative.
Preferably, the energy storage unit comprises a power battery and a super capacitor,
Presetting the working boundary of the SOC values of the power battery and the super capacitor to 40% -90%;
Setting a charging and discharging strategy: when the SOC is less than or equal to 40%, the power battery and the super capacitor start to charge, and when the SOC of the energy storage unit is more than or equal to 90%, the power battery and the super capacitor end to charge and start to discharge;
The charging and discharging strategy is defined as an active charging and discharging strategy, the charging and discharging state of the energy storage unit determined by power distribution is a passive charging and discharging strategy, and when the active charging and discharging strategy collides with the passive charging and discharging strategy, the active charging and discharging strategy obeys the passive charging and discharging strategy.
Preferably, the electromechanical liquid coupling unit adopts a variable pump and a quantitative motor hydraulic system, the output rotating speed of the quantitative motor is controlled on the basis of ensuring the normal output of torque by adjusting the displacement of the variable pump, and a double closed-loop speed regulating system is adopted to control the rotating speed and stably run the motor;
and taking the total efficiency as a principle of optimal efficiency, taking the rotating speed of the motor and the torque to be distributed as input of fuzzy control, taking the torque of the motor as output, and carrying out distribution regulation and control on the torques of the motor and the motor.
The invention has at least the following beneficial effects:
1. the quantity of the engines working in the power unit under different working conditions is determined according to the required power, the self characteristics of the engines are combined, the fuel consumption is reduced, and the power unit is ensured to work at the highest efficiency point all the time.
2. The energy storage unit fully considers the self characteristics of the power battery and the super capacitor, and the SOC working high-efficiency area of the power battery and the super capacitor is considered, so that an active charge-discharge strategy is formulated, the working boundary of the energy storage unit is defined, and the energy storage unit is ensured to always work at the highest efficiency point.
3. The electromechanical liquid coupling unit realizes the control of the rotating speed and the stable operation of the motor through a double closed loop speed regulating system, adopts fuzzy control, distributes required torque based on the principle of optimal total efficiency, reasonably regulates the torque distribution according to different road conditions, and realizes the optimal output combination of mechanical energy, electric energy and hydraulic energy.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
In order to make the objects, technical solutions and advantageous effects of the present invention more clear, the present invention provides the following drawings for description:
FIG. 1 is a schematic illustration of a hybrid powertrain energy management strategy targeting overall efficiency optimization in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a target power adaptive allocation algorithm according to an embodiment of the present invention;
FIG. 3 is a flowchart of an adaptive power allocation Algorithm (AUTO) according to embodiments of the invention;
FIG. 4 is a flow chart of an average allocation Algorithm (AVE) in accordance with one embodiment of the present invention;
FIG. 5 is a flow chart of an improved particle swarm Algorithm (APSO) according to an embodiment of the invention;
FIG. 6 is a flowchart of a Genetic Algorithm (GA) in accordance with an embodiment of the present invention;
FIG. 7 is a graph showing the comparison of the algorithm solving efficiency and the full working condition in the embodiment of the invention;
FIG. 8 is a graph showing the algorithm solving time full condition comparison in an embodiment of the present invention;
fig. 9 is a schematic diagram illustrating a charge and discharge strategy of an energy storage unit according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The energy management strategy of the hybrid power system with the optimal comprehensive efficiency as the target is provided by the invention, and referring to fig. 1, aiming at the hybrid power system, the hybrid power system is composed of a power unit, an energy storage unit and an electromechanical liquid coupling unit, so that the management of power flow and energy flow with the optimal comprehensive efficiency as the target of the power system is realized. Each engine in the power unit works independently, and flexible power output combination can be realized between the cylinders; the energy storage unit is introduced into the super capacitor, and the power battery and the super capacitor carry out establishment of a charge-discharge strategy according to the physical characteristics of the power battery and the super capacitor; the electromechanical liquid coupling unit is constructed based on the design of the hydraulic motor and the motor, and can flexibly output mechanical energy, electric energy and hydraulic energy according to different energy requirements, so that the energy requirements of a power system under different working conditions are met. Aiming at the improvement of the current hybrid power system module architecture, the super capacitor is added to the energy storage unit, so that the target power can be better decomposed to bear high-frequency power and low-frequency power; perfecting the energy output form and realizing the multi-element energy coupling output of mechanical energy, electric energy and hydraulic energy.
In a preferred embodiment, and referring to FIGS. 1-3, the hybrid powertrain energy management strategy targets an overall efficiency optimization. The key parameters of the power unit such as fuel injection quantity, fuel consumption rate and the like are taken as adjustment quantity, the power unit output power and efficiency are taken as controlled quantity to construct a MAP (MAP) graph of the power unit output power and efficiency, and the output power of the highest point of the power unit efficiency is determined;
And carrying out distribution calculation on the obtained target required power according to high and low optimal power calculation points based on a preset self-adaptive distribution optimization algorithm of the target power of the power unit. The output power of the power unit is only an integral multiple of the output power of the optimal efficiency point, so that the problem that the power unit outputs surplus or deficient power when facing different required power exists, and the power battery is required to perform peak clipping and valley filling. The power output by the power unit is charged by the power battery, and the power unit output power is empty to be supplemented by the power battery, because the self-adaptive distribution optimization algorithm of the power unit target power is divided into two ways of high and low optimal power matching, the total efficiency of the power unit is optimal as a principle, the final result obtained by comparing which power distribution algorithm is better, thereby realizing the overall efficiency of the power unit under different required powers to be always optimal, wherein the optimal power unit efficiency is ensured to always work at the highest efficiency point, and otherwise, the power unit is forbidden to work. For example, the rated output power of the selected engine is 30kW, and the engine efficiency is optimal when the output power of the selected engine is 25kW after the power and efficiency MAP are checked. Therefore, the power unit output power is always specified to be an integer multiple of 25kW, otherwise the power unit is not operating. If the target required power is 120kW, there are two operating conditions. The mode 1 and 5 engines work simultaneously, 125kW of power is output, 5kW of surplus power exists, and the surplus 5kW of power is used for charging the power battery; and the mode 2 and the mode 4 engines work simultaneously, output 100kW of power, and then 20kW of power is available, and the available power is output by the power battery in a complementary mode. Compared with the two modes, which mode has higher power system efficiency and is oriented to different required powers, the algorithm flow is shown in figure 2. The working modes of the highest power unit efficiency point and the high and low optimal power calculation points are explained, and the working modes can be understood that when the output power of the power unit is higher than the required power, the residual power charges the battery; when the output power of the power unit is lower than the required power, the insufficient power is supplemented by the battery.
In a preferred embodiment, referring to fig. 3, the target power adaptive allocation algorithm first collects test data of the power unit to make a MAP image, and then obtains a power-efficiency relationship curve of the power unit to obtain an optimal working point, develops a unit allocation algorithm according to the optimal working point of the power unit, so that more power is allocated to a power value corresponding to the optimal working point as much as possible, then dynamically optimizes allocated power which does not fall on the power value corresponding to the optimal working point, and finally selects an optimal allocation scheme through multiple iterations to perform power control and energy output on the power unit.
In a preferred embodiment, referring to fig. 4, the power module is directly and averagely distributed to each power unit (the total power is divided by the number of engines in the power unit) according to the target required power by an average distribution algorithm, and each power unit adjusts the control parameter oil injection quantity and the load factor according to the average power signal to realize power output of the power module.
In a preferred embodiment, referring to fig. 5, the power unit power distribution is optimized by improving the particle swarm algorithm, the improved particle swarm algorithm flow comprises:
the method comprises the steps that firstly, the speed and the position of particles are randomly set within an allowable range;
a second step of calculating a particle fitness value based on a given condition or formula; thirdly, updating the current optimal position and the global optimal position through particle fitness value comparison;
thirdly, in each iteration process, the speed and the position of the particle are updated through the individual extremum and the group extremum;
Wherein, the optimizing formula is:
Wherein, For the next iteration particle velocity,/>Is the position of the particle,/>For the position of the next iteration particle,/>Is an inertial weight; /(I)The historical optimal position of the current particle; /(I)A historical optimal position for the population of particles; k is the current iteration number; /(I)Is the velocity of the particles; /(I)And/>Is a preset acceleration constant; /(I)And/>Two mutually independent random numbers distributed in the interval [0,1 ];
And finally, searching an individual extremum and a population extremum according to the particle fitness value in the new population. Until its fitness value or maximum number of iterations reaches the effect. And (3) dynamically adjusting an acceleration constant and an inertia weight to obtain an improved particle swarm algorithm, and fusing a penalty function to establish constraint that the sum of the distributed power is equal to the target required power for optimizing, so that the optimal control of power distribution of the power unit is realized.
In a preferred embodiment, referring to fig. 6, the power distribution of the power unit is optimized by a genetic algorithm, which simulates the phenomena of replication, crossover and mutation occurring in natural selection and inheritance, and from any initial population, a group of individuals more suitable for the environment is generated by random selection, crossover and mutation operation, so that the group evolves to a better and better area in the search space, the continuous reproduction and evolution of the first generation finally converges to a group of individuals most suitable for the environment, and the optimal solution of the problem is obtained. And meanwhile, the constraint of the sum of the power distribution is introduced into the penalty function idea, and the optimal power distribution scheme is found by carrying out multi-round iterative optimization so as to control the power output of the power unit.
The overall efficiency of the power unit is optimal, and the final result obtained by comparing the power distribution algorithms is better, so that the overall efficiency of the power unit under different required powers is always optimal, and the power unit is always the main body of the hybrid power system, so that the power unit is ensured to always work at the highest efficiency point. Through the analysis, the output power of the power unit is always kept to be an integer multiple of 25 kW. The four algorithms introduced above are compared in efficiency with solving time under all conditions of 0-180kW of required power. By observing the full-working-condition comparison chart of the algorithm solving efficiency, referring to fig. 7, the average distribution algorithm (ave), the improved particle swarm algorithm (apso) and the genetic algorithm (ga) can be obtained, when the required power is low, the comprehensive efficiency solved by the distribution power is low, because all power units are used for outputting, which is caused by the fact that the fuel consumption is large, and the self-adaptive power unit power distribution algorithm (auto) fuses the working characteristics of the power units, and can be used for obtaining the optimal comprehensive efficiency distribution scheme under the full working condition through comparison. And (3) observing an algorithm solving time full-working-condition comparison graph, referring to fig. 8, when different power demands are met, the MATLAB program running solving time of the improved particle swarm algorithm (apso) reaches about 4.5s, the MATLAB program running solving time of the genetic algorithm (ga) is about 8s, and the MATLAB program running time of the self-adaptive power unit power distribution algorithm (auto) and the average distribution algorithm (ave) is greatly reduced to be less than 0.5s, so that a real-time control strategy can be better realized. For the comparison of the two points, the self-adaptive power unit power distribution algorithm (auto) combines the characteristics of a modularized power system, the energy is efficiently matched, and the comprehensive solving effect is optimal.
In a preferred embodiment, referring to fig. 9, the energy storage unit is composed of a power battery with high energy density and a super capacitor with high power density, so that performance characteristics of the power battery and the super capacitor are fully utilized, and high-energy output of the energy storage unit is achieved. And regulating and controlling the bus voltage by adopting a PI algorithm, maintaining the balance of the bus voltage, regulating and controlling the high-low frequency current by adopting a frequency domain distribution strategy, and distributing the high-frequency power to the super capacitor and distributing the low-frequency power to the power battery. The performance advantages of the power battery and the super capacitor can be fully exerted, and the service life of the power battery can be ensured. In order to meet the above target requirements, the high-frequency power and the low-frequency power of the power system are distributed, the high-frequency power is borne by the super capacitor, and the low-frequency power is jointly borne by the power battery and the power unit. The power distribution is regulated to be positive, and the composite energy storage unit outputs energy outwards; and when the distribution power is negative, the composite energy storage unit charges.
In a preferred embodiment, referring to fig. 9, there is a high efficiency zone for the power battery and the supercapacitor SOC, the operating boundary of both SOCs is set to 40% -90%, and the composite energy storage only operates within this range. Setting a charge-discharge strategy, and starting to charge the power battery and the super capacitor when the SOC is less than or equal to 40%; when the SOC of the energy storage unit is more than or equal to 90%, the power battery and the super capacitor finish charging and start discharging. The formulated charging and discharging strategy is defined as an active charging and discharging strategy, and the charging and discharging states of the energy storage unit determined by power distribution are passive charging and discharging strategies. When the active charge-discharge strategy collides with the passive charge-discharge strategy, the active charge-discharge strategy is subject to the passive charge-discharge strategy. The passive charge-discharge strategy is determined by the power allocation, and therefore, the passive charge-discharge strategy has higher priority. The comprehensive efficiency of the energy storage unit is ensured by always keeping the SOC of the energy storage unit between 40% and 90% of the high-efficiency area, and the comprehensive efficiency of the power system is further improved.
In a preferred embodiment, referring to fig. 9, the energy storage unit capacity is determined in such a way as to achieve an optimal design of the volume and mass of the energy storage unit. The capacity of the energy storage unit, i.e. the energy stored by the energy storage unit, is designed by an energy back-pushing method. And (3) distributing power based on the power battery and the super capacitor, and integrating time to obtain the energy consumed by the power battery and the super capacitor in one working cycle under a specified road spectrum. The maximum charge and discharge power of the power battery and the super capacitor is instantaneously distributed, so that the minimum capacity of the energy storage unit can be known according to the relation between the charge and discharge multiplying power and the charge and discharge power. And by combining an active charge-discharge strategy, the low-capacity energy storage unit is ensured to meet the requirement of the hybrid power system on power output. The power battery and the super capacitor are designed in a volume and quality light-weight mode by combining the charging and discharging strategies of the energy storage unit, and the minimum capacity is determined as small as possible on the premise that the energy output of the energy storage unit is met, so that the determination of the types of the sub-unit battery and the capacitor of the energy storage unit is made as a basis.
In a preferred embodiment, the electromechanical liquid coupling unit adopts a variable pump and a quantitative motor hydraulic system, and the output rotating speed of the quantitative motor is controlled on the basis of ensuring the normal output of the torque by adjusting the displacement of the variable pump. And a double closed-loop speed regulating system is adopted to realize the control of the rotating speed and the stable operation of the motor. And taking the total efficiency as a principle of optimal total efficiency, taking the rotating speed of the motor and the torque to be distributed as input of fuzzy control, and taking the torque of the motor as output, thereby realizing the torque distribution regulation and control of the motor and the motor. According to different power requirements, flexible combined output of mechanical energy, electric energy and hydraulic energy is realized, and the aim of optimal comprehensive efficiency of the power system is fulfilled. Thereby realizing flexible output of mechanical energy, electric energy and hydraulic energy.
Finally, it is noted that the above-mentioned preferred embodiments are only intended to illustrate rather than limit the invention, and that, although the invention has been described in detail by means of the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention as defined by the appended claims.
Claims (3)
1. A hybrid system energy management strategy targeting integrated efficiency optimization, comprising:
Determining a power unit, an energy storage unit and an electromechanical liquid coupling unit which are divided in advance in a hybrid power system, and determining target required power required to be output by the hybrid power system;
For the power unit, distributing target required power based on the output power of the power unit under the condition of optimal efficiency based on a preset distribution algorithm, and controlling the output of the power unit according to a distribution result;
For the energy storage unit, regulating and controlling the busbar voltage by adopting a PI algorithm, and distributing high-frequency power to the super capacitor and low-frequency power to the power battery by adopting a strategy of frequency domain distribution;
For the electromechanical liquid coupling unit, a variable pump and a quantitative motor hydraulic system are adopted, and the output rotating speed of the quantitative motor is controlled on the basis of ensuring the normal output of the torque by adjusting the displacement of the variable pump;
the preset allocation algorithm comprises the following steps:
Dividing the target required power by the optimal output power of the power unit under the optimal efficiency condition to obtain a first multiple value and a first residual value, and taking the first multiple value and the first residual value as a first type of calculation result;
adding one to the first multiple value to obtain a second multiple value, subtracting the first residual value from the optimal output power to obtain a second residual value, and obtaining a second class calculation result according to the second multiple value and the second residual value;
determining a low-power distribution strategy according to the first type of calculation result, and calculating the first total efficiency of the power system under the low-power distribution strategy;
determining a high-power distribution strategy according to the second class of calculation results, and calculating the second total efficiency of the power system under the high-power distribution strategy;
comparing the first total efficiency with the second total efficiency, and determining an allocation strategy with the highest total efficiency as an allocation result;
the controlling the output of the power unit according to the distribution result comprises:
Determining a high/low power allocation strategy corresponding to the allocation result, and determining a corresponding calculation result based on the high/low power allocation strategy;
determining a corresponding multiple value according to the calculation result, and selecting a corresponding number of power units according to the multiple value to perform output control according to the optimal output power;
Determining a corresponding residual value according to the calculation result, distributing power corresponding to the residual value output by the power battery to charge the power battery when the distribution result corresponds to a high-power distribution strategy, and outputting power corresponding to the residual value by the power battery to supplement output power when the distribution result corresponds to a low-power distribution strategy;
the preset allocation algorithm further comprises:
Collecting test data of a power unit, generating an MAP image, selecting an optimal efficiency point according to the MAP image, and obtaining a relation curve according to the optimal efficiency-power point;
Solving an optimal working point according to the relation curve, and maximally distributing the target required power to a power value corresponding to the optimal working point based on a preset sub-unit algorithm according to the optimal working point of the power unit;
for the unassigned residual power in the required power, carrying out distribution optimizing on the residual power through a preset optimizing algorithm, and finally selecting an optimal distribution scheme through multiple iterations to carry out power control and energy output on the power unit;
The electromechanical liquid coupling unit adopts a variable pump and a quantitative motor hydraulic system, controls the output rotating speed of the quantitative motor on the basis of ensuring the normal output of torque by adjusting the displacement of the variable pump, and adopts a double closed-loop speed regulating system to control the rotating speed and stably run the motor;
and taking the total efficiency as a principle of optimal efficiency, taking the rotating speed of the motor and the torque to be distributed as input of fuzzy control, taking the torque of the motor as output, and carrying out distribution regulation and control on the torques of the motor and the motor.
2. The hybrid system energy management strategy targeting optimal overall efficiency according to claim 1, wherein the energy storage unit consists of a high energy density power cell and a high power density super capacitor;
regulating and controlling the bus voltage by adopting a PI algorithm, and controlling the balance of the bus voltage;
the method comprises the steps of carrying out high-frequency and low-frequency power distribution on target required power of a power system by adopting a strategy of frequency domain distribution, distributing high-frequency power to a super capacitor for bearing, and distributing low-frequency power to a power battery and a power unit for bearing together;
the energy storage unit outputs energy outwards when the allocated power is positive, and receives the external energy and enters a charging state when the allocated power is negative.
3. A hybrid powertrain energy management strategy targeted for overall efficiency optimization as recited in claim 2, wherein the energy storage unit comprises a power cell and a super-capacitor,
Presetting the working boundary of the SOC values of the power battery and the super capacitor to 40% -90%;
Setting a charging and discharging strategy: when the SOC is less than or equal to 40%, the power battery and the super capacitor start to charge, and when the SOC of the energy storage unit is more than or equal to 90%, the power battery and the super capacitor end to charge and start to discharge;
The charging and discharging strategy is defined as an active charging and discharging strategy, the charging and discharging state of the energy storage unit determined by power distribution is a passive charging and discharging strategy, and when the active charging and discharging strategy collides with the passive charging and discharging strategy, the active charging and discharging strategy obeys the passive charging and discharging strategy.
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