A distributed modular hybrid system overall design method

Abstract

The application discloses a kind of overall design methods of distributed modular hybrid system, it is related to power system design field.The method determines the number of multiple energy conversion units and the number of energy storage units corresponding to each ratio scheme according to the number of power unit and different ratio scheme;Simulation model of each design scheme is constructed, and demand power is distributed by power distribution algorithm, and each simulation model is simulated under preset environmental conditions, wherein the power distribution algorithm is assisted by energy storage unit, and high and low frequency demand power is flexibly distributed;Based on the simulation results, the best design scheme with the highest average efficiency is determined.The application is designed according to different ratio scheme, analyzes the global result of different combination scheme, obtains the best design scheme, improves the overall average efficiency of power system.In addition, the power distribution algorithm intelligently adjusts according to energy demand and flexible combination, improves the space utilization and the availability of power system.

Description

Technical Field

[0001] This invention relates to the field of power system design technology, and more specifically, to a method for overall design of a distributed modular hybrid system. Background Technology

[0002] A challenge in practical applications for single-engine systems is that they cannot always operate within their optimal operating range. This is because the engine's performance characteristics dictate that it can only achieve maximum efficiency at a specific operating point, and this optimal operating point is often unique. In variable operating environments, the engine's load conditions are constantly changing, which means that single-engine systems cannot maintain optimal efficiency in many situations.

[0003] Modular hybrid powertrain systems are an advanced powertrain design that achieves greater efficiency and flexibility by breaking down the entire system into multiple independent working modules. The core of this system lies in its modular architecture, which allows each component to operate independently according to different operational needs, thereby optimizing overall performance. Modular hybrid powertrains exhibit unique advantages, particularly in engine operation. In this system, each module is an independently operating unit, capable of optimization for specific operating conditions. This means that different parts of the modular hybrid powertrain can achieve optimal efficiency at different operating points. Therefore, the matching and design of subsystems are fundamental to modular hybrid powertrains, while the internal parameters and architecture of the powertrain all influence its performance. Thus, improving the average efficiency and overall performance of hybrid powertrains is a pressing issue in current hybrid powertrain design. Summary of the Invention

[0004] In view of this, the present invention provides a distributed modular hybrid system overall design method, which analyzes the global results of different combination schemes to obtain the optimal design scheme of hybrid power system architecture, improves the overall average efficiency of the power system, and performs intelligent allocation according to energy demand and flexible combination, thereby improving space utilization and the availability and durability of the power system.

[0005] To achieve the above objectives, the following solution is proposed:

[0006] A distributed modular hybrid system overall design method, the hybrid system including a power unit, an energy storage unit and a multi-element energy conversion unit, the design method includes the following steps:

[0007] Based on the number of power units and different ratio schemes, determine the number of multi-element energy conversion units and energy storage units corresponding to each ratio scheme, and obtain the design scheme set;

[0008] Simulation models of each design scheme in the design scheme set are constructed. The required power is allocated through a power allocation algorithm. Simulations are performed on each simulation model under preset environmental conditions to obtain the simulation results of each simulation model. The power allocation algorithm is assisted by energy storage units to flexibly allocate high and low frequency required power.

[0009] The optimal design scheme with the highest average efficiency is determined based on simulation results.

[0010] Preferably, the formulation includes:

[0011] The ratio schemes of the power unit and the multi-element energy conversion unit are 6:1, 4:1, 3:1, 2:1 and 1:1, respectively;

[0012] The power unit and energy storage unit ratio schemes are 6:1, 4:1, 3:1, 2:1 and 1:1, respectively.

[0013] Preferably, the energy storage unit includes a supercapacitor and a power battery.

[0014] Preferably, the power allocation algorithm flexibly allocates high and low frequencies, comprising:

[0015] The power unit serves as the primary power output, while the energy storage unit provides auxiliary output based on the filtering concept.

[0016] Preferably, the process of using the power unit as the main power output and the energy storage unit providing auxiliary output based on filtering principles includes:

[0017] Supercapacitors require high-frequency power output;

[0018] The power unit outputs low-frequency power at its optimal power value, while the remaining power is supplied by the power battery.

[0019] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0020] The distributed modular hybrid system overall design method provided by this invention first determines the number of multi-element energy conversion units and energy storage units corresponding to each power unit ratio scheme based on the number of power units and different ratio schemes, thus obtaining a set of design schemes. Then, simulation models of each design scheme in the set are constructed, and the required power is allocated using a power allocation algorithm. Simulations are performed on each model under preset environmental conditions to obtain simulation results. The power allocation algorithm uses energy storage units as an aid to flexibly allocate high- and low-frequency required power. Finally, the optimal design scheme with the highest average efficiency is determined based on the simulation results. This invention designs based on different ratios, performs simulations based on a power allocation algorithm, analyzes the global results of different combinations, and obtains the optimal design scheme for the hybrid power system architecture, improving the overall average efficiency of the power system and achieving efficient operation of the modular hybrid power system.

[0021] The power allocation algorithm of this invention intelligently allocates power based on energy demand and flexible combination, which improves space utilization and can provide redundancy for the power system to improve its availability and durability. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 This is a structural block diagram of a distributed modular hybrid system provided in an embodiment of the present invention;

[0024] Figure 2 A flowchart illustrating the overall design method of a distributed modular hybrid system provided in this embodiment of the invention;

[0025] Figure 3 This is a schematic diagram of a set of design schemes provided in the embodiments of the present invention;

[0026] Figure 4 This is a schematic diagram of the connection relationship between the units of the simulation model provided in the embodiments of the present invention;

[0027] Figure 5 This is a schematic diagram of the simulation results of the simulation model provided in the embodiment of the present invention;

[0028] Figure 6 A schematic diagram illustrating the basic energy demand allocation rules for an energy storage unit provided in an embodiment of the present invention;

[0029] Figure 7This is a power distribution diagram of the power unit-battery-capacitor in embodiment 1 of the present invention;

[0030] Figure 8 This is a state-of-charge diagram of the battery and capacitor in embodiment 1 of the present invention;

[0031] Figure 9 This is a diagram of the distributed modular hybrid system in embodiment 1 of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] First, combined Figure 1 The hybrid system of the present invention will be described in the following embodiments: Figure 1 As shown, the hybrid system mainly includes a power unit, an energy storage unit, and a multi-element energy conversion unit. The energy storage unit includes supercapacitors and power batteries (storage batteries), while the multi-element energy conversion unit includes inverters and motors.

[0034] Next, in conjunction with the embodiments of the present invention Figure 2 This paper introduces the overall design methodology for distributed modular hybrid systems, such as... Figure 2 As shown, the design method includes the following steps:

[0035] Step S01: Based on the number of power units and different ratio schemes, determine the number of multi-element energy conversion units and the number of energy storage units corresponding to each ratio scheme.

[0036] Specifically, different numbers of power units, energy storage units, and multi-element energy conversion units can be combined, resulting in numerous different options and possibilities for the hybrid system's combination schemes. After determining the number of power units, different numbers of multi-element energy conversion units paired with power units yield schemes with different ratios of multi-element energy conversion units, and different numbers of energy storage units paired with power units yield schemes with different ratios of energy storage units. The ratios of power units to multi-element energy conversion units are 6:1, 4:1, 3:1, 2:1, and 1:1; the ratios of power units to energy storage units are also 6:1, 4:1, 3:1, 2:1, and 1:1. For example, when the number of power units is 12, the number of multi-element energy conversion units can be 2, 3, 4, 6, and 12, and the number of energy storage units can be 2, 3, 4, 6, and 12. Therefore, the design scheme set contains 25 design schemes, as shown in the example. Figure 3 As shown.

[0037] Step S02: Construct simulation models of each design scheme in the design scheme set, allocate the required power through a power allocation algorithm, and simulate each simulation model under preset environmental conditions.

[0038] Specifically, simulation models of each design scheme are built in the Matlab-Simulink interface, where each simulation model allocates the required power using a power allocation algorithm. Simulations are then performed on each simulation model under a preset environment.

[0039] Power Unit Module: The power unit consists of a free piston linear motor and subsequent AC / DC rectification stages. Based on the working principle of the free piston linear motor, a mathematical model is established and transformed into a zero-dimensional simulation model using the graphical programming capabilities of the Matlab / Simulink platform; the input can be a selectable road spectrum, and the altitude and temperature of the environment can be set.

[0040] Energy Storage Unit Module: A lithium-ion battery is selected as the individual unit of the battery pack in the energy storage unit. It is modeled in Simulink, with the battery model representing the battery pack itself. The parameters of the battery pack are adjusted to reflect the number of series and parallel connections. A double-layer capacitor is selected as the individual unit of the supercapacitor pack in the composite energy storage system. It is modeled in Simulink, with the supercapacitor model representing the supercapacitor pack itself. The parameters of the supercapacitor pack can be set by directly adjusting the parameters of the supercapacitor model, allowing for the setting of the individual unit's rated voltage, rated capacity, and the number of series and parallel connections.

[0041] Multi-electro-energy conversion unit module: The multi-electro-energy conversion unit consists of a hydraulic motor and a coaxial electric motor. The two motors couple the rotation driven by electrical energy and hydraulic energy through planetary gears to output mechanical energy, thus realizing the output of electromechanical-hydraulic coupled energy.

[0042] Output module: View the output results (such as power distribution, SOC, etc.) of the power unit, energy storage unit, etc.

[0043] The connection relationships between each unit module are as follows: Figure 4 As shown, the output of the power unit module is transmitted to the output module, the output of the battery capacitor section within the power unit is transmitted to the energy storage unit module and the output module, and the output of the energy storage unit module is transmitted to the output module. Finally, the output module outputs the result to the multi-element energy conversion unit module, where the output of the output module is the sum of the outputs of the power unit and the energy storage unit. For example, simulation models of various design schemes are performed using Matlab-Simulink under environmental conditions of 20 degrees Celsius and 0 meters altitude, yielding the following results: Figure 5 The simulation results of the simulation models of each technical solution are shown.

[0044] The power allocation algorithm intelligently allocates power based on energy demand and flexible combinations, with energy storage units providing assistance, to flexibly distribute high- and low-frequency power demands. Leveraging the fast-discharge and fast-charging characteristics of supercapacitors, high-frequency power demands are output by the supercapacitors, while low-frequency power demands are output by the power unit and battery according to the allocation algorithm. Since the power unit of the hybrid system is the primary power output system, the battery and supercapacitor of the energy storage unit play auxiliary roles. Therefore, the core of low-frequency power demand allocation is to prioritize ensuring the power unit operates at its optimal efficiency point, outputting power at that point, with the remaining power demand supplemented by the battery. The basic energy demand allocation rules of the energy storage unit based on filtering principles are as follows: Figure 6 As shown, select the required motor power. and the state of charge of supercapacitors These are the two key parameters of this allocation rule. and These represent the minimum and maximum states of charge of a supercapacitor.

[0045] Determine the required power of the motor Is it greater than zero? If the motor requires power... If the value is greater than zero, the vehicle is in a driving state; otherwise, it is in a braking state.

[0046] When the motor requires power When the value is greater than zero, if the motor requires power Greater than or equal to the set positive motor demand power ,and The power battery and supercapacitor work together to provide power to drive the vehicle. The output power of the power battery... After a certain time delay due to a first-order filter function, the power is slowly supplied to the vehicle, and the remaining power is supplied by the output power of the supercapacitor. Provide; when At this time, the supercapacitor's energy is insufficient, and the power required by the motor is entirely provided by the power battery alone.

[0047] If the motor requires power Less than the set positive motor demand power And the state of charge of the supercapacitor Less than the target state of charge of the supercapacitor calculated based on velocity constraints Because the motor requires relatively low power, the power battery, in addition to providing power to drive the pure electric vehicle, also needs to provide charging power to replenish the supercapacitor for high-power applications such as acceleration or hill climbing; when At this time, the supercapacitor does not work, and the power battery alone provides all the necessary power for the pure electric vehicle to run.

[0048] When the motor requires power When the power requirement is less than zero, if the motor requires power Less than or equal to the set negative motor power demand ,Right now ,and The supercapacitor does not absorb regenerative braking energy; it only charges the power battery. During charging, the power battery is slowly charged after a certain time delay following a first-order filter function to prevent high-power charging from damaging the battery. The impact damage caused; and when In this case, priority is given to supplying supercapacitors. Charge it.

[0049] If the motor requires power Greater than the set negative power demand of the motor ,Right now ,and In this case, the supercapacitor bank does not absorb regenerative braking energy, but only charges the power battery pack. Since the negative power is small, charging through a first-order filter function is not required. In this case, the supercapacitor is charged first. This can be achieved by slowing down the charging of the power battery by applying the feedback power through a first-order filter function with a certain time lag. The power allocation is the same under the same conditions.

[0050] Figure 7 The diagram shows the power distribution of the power unit, battery, and capacitor in Scheme 1, where P_bat is the power of the power battery, P_b is the power of the power unit, and P_sc is the power of the supercapacitor. Figure 8 The state of charge (SOC) diagrams for the battery and capacitor in Scheme 1 are shown.

[0051] Step S03: Determine the optimal design scheme with the highest average efficiency based on the simulation results.

[0052] Specifically, the design scheme with the highest average efficiency is selected based on the average power obtained from each simulation model. For example... Figure 4 As shown, the design scheme with the highest average efficiency is Scheme 1, with a theoretical average efficiency of 75.9208%. Scheme 1's multi-element energy combination consists of 12 power units paired with 2 sets of multi-element energy sources (6 units to 1 unit), and its energy storage combination also consists of 12 power units paired with 2 sets of energy storage sources (6 units to 1 unit). Based on Scheme 1, the following results are obtained... Figure 9 The diagram shows a distributed modular hybrid system.

[0053] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0055] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for overall design of a distributed modular hybrid system, characterized in that, Hybrid systems include a power unit, an energy storage unit, and a multi-energy conversion unit. The design method includes the following steps: Based on the number of power units and different ratio schemes, determine the number of multi-element energy conversion units and energy storage units corresponding to each ratio scheme, and obtain the design scheme set; Simulation models of each design scheme in the design scheme set are constructed. The required power is allocated through a power allocation algorithm. Simulations are performed on each simulation model under preset environmental conditions to obtain the simulation results of each simulation model. The power allocation algorithm is assisted by energy storage units to flexibly allocate high and low frequency required power. Determine the optimal design scheme with the highest average efficiency based on simulation results; The energy storage unit includes a supercapacitor and a power battery; The power allocation algorithm performs a flexible allocation of high and low frequencies, including: The power unit serves as the primary power output, while the energy storage unit provides auxiliary output based on filtering principles. When the motor's power demand is greater than zero and greater than the set positive power demand of the motor, if the supercapacitor's state of charge is greater than or equal to the minimum state of charge, the power battery and the supercapacitor jointly provide power to drive the vehicle. The power battery's output power is supplied after a certain time lag through a first-order filter function, and the remaining power is provided by the supercapacitor's output power. If the supercapacitor's state of charge is less than the minimum state of charge, the required power is provided entirely by the power battery alone. When the motor's power demand is greater than zero but less than the set positive power demand of the motor, if the state of charge of the supercapacitor is less than the target state of charge, the power battery needs to supply power to both the electric vehicle and the supercapacitor simultaneously; if the state of charge of the supercapacitor is greater than or equal to the target state of charge, the power battery alone provides all the required power to drive the electric vehicle. When the motor's required power is less than zero, or when the motor's required power is greater than or equal to the set negative power requirement of the motor, if the supercapacitor's state of charge is greater than or equal to its maximum state of charge, then the power battery will be charged; if the supercapacitor's state of charge is less than its maximum state of charge, then the supercapacitor will be charged. When the motor's power demand is less than zero, or greater than the set negative power demand of the motor, if the supercapacitor's state of charge is greater than or equal to its maximum state of charge, the power battery will be charged; if the supercapacitor's state of charge is less than its maximum state of charge, the supercapacitor will be charged, and the feedback power will be used to charge the power battery after a certain time delay through a first-order filter function.

2. The overall design method for a distributed modular hybrid system according to claim 1, characterized in that, The formulation scheme includes: The ratio schemes of the power unit and the multi-element energy conversion unit are 6:1, 4:1, 3:1, 2:1 and 1:1, respectively; The power unit and energy storage unit ratio schemes are 6:1, 4:1, 3:1, 2:1 and 1:1, respectively.

3. The overall design method for a distributed modular hybrid system according to claim 1, characterized in that, The process of using the power unit as the main power output and the energy storage unit as an auxiliary output based on the filtering concept includes: Supercapacitors require high-frequency power output; The power unit outputs low-frequency power at its optimal power value, while the remaining power is supplied by the power battery.

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