Amphibious hybrid power amphibious vehicle sailing power distribution method based on PMP optimization

Abstract

The invention relates to the technical field of amphibious hybrid power equipment, in particular to an amphibious hybrid power amphibious vehicle navigation power distribution method based on PMP optimization, and the method comprises the steps: constructing an amphibious hybrid power system power source output power relation; based on a PMP theory, constructing a Hamiltonian function of reversible motor power; the dynamic switching condition of the operation mode is determined based on the Hamiltonian function of the reversible motor power, the optimal working value of the final control variable reversible motor power Pm and the optimal working value of the engine power Peng are determined, the key factor that the working change of the power source can induce the change of the switching condition is fully considered, and the problem that the distribution effect is poor due to the fixed switching condition is solved. The Pontryagin minimum principle (PMP) is introduced to optimize the switching condition in real time, and the overall operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of amphibious hybrid power equipment, and in particular to a navigation power distribution method for an amphibious hybrid power amphibious vehicle based on PMP optimization. Background Art

[0002] The power allocation methods of amphibious hybrid power systems mainly include rule-based, frequency-based, global optimization-based, and instantaneous optimization-based methods. The rule-based power allocation method is widely used because of its simple algorithm and easy implementation, but the setting process is overly dependent on engineering experience, and if the switching conditions are not set reasonably, it will seriously affect the allocation effect.

[0003] Although the current power allocation method can allocate power to the power source by setting the switching conditions, it does not fully consider the key factor that the working change of the power source can induce the change of the switching conditions, which limits the optimal power allocation. Therefore, in order to solve the problem of poor allocation effect caused by fixed switching conditions, the Pontryagin Minimum Principle (PMP) is introduced to optimize the switching conditions in real time and improve the overall operating efficiency. Summary of the invention

[0004] In view of the above problems, a navigation power distribution method for amphibious hybrid vehicle based on PMP optimization was proposed.

[0005] Therefore, the technical problem solved by the present invention is that the rule-based power allocation algorithm has been widely used in the power allocation of hybrid power systems, but the setting of the rules is overly dependent on engineering experience, and the overall operation effect is poor. This patent will use the PMP algorithm to optimize the static switching conditions of the rules, so that it can be adjusted in real time based on the status of the equipment, obtain dynamic switching conditions, and improve the optimization effect of the entire system.

[0006] The implementation of the present invention comprises the following steps:

[0007] 1. Construct the power output relationship of the power source of the amphibious hybrid power system, including:

[0008] Build required power P ref With engine power P eng , reversible motor power P m The relationship is shown in formula (1).

[0009] P eng =P ref -P m (1)

[0010] Build battery power P bat With reversible motor power P m The relationship is shown in equations (2)-(3).

[0011]

[0012]

[0013] Where P ref is the required power, P eng is the engine power, P m is the reversible motor power, P bat is the battery power, η m is the working efficiency of the reversible motor, P bat,loss To consume power for the battery, Where V oc is the open circuit voltage of the battery, and R is the internal resistance of the battery.

[0014] Build engine power P eng With fuel release power P fuel The relationship between them is shown in formula (4).

[0015]

[0016] Where P fuel Power released for fuel, P eng,loss is the friction loss power of the engine, and e is the thermal efficiency of the engine.

[0017] 2. Based on the PMP theory, the Hamiltonian function of the reversible motor power is constructed, as shown in formula (5).

[0018]

[0019] Where H(P m ) is the reversible motor power P m Hamiltonian function, δ is the engine working state, and s is the dynamic coordination factor.

[0020] When the amphibious hybrid vehicle is in the navigation state, it can be divided into hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode according to the working conditions of the power source. Based on the Hamiltonian function of formula (5), the Hamiltonian expression under different working modes can be derived as shown in formula (6).

[0021]

[0022] Where H 1，2,3,4 They represent the Hamiltonian function of the hybrid power system when it works in hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode. In order to find the minimum control P of the Hamiltonian function (Eq. (6)), m , we need to further analyze the Hamiltonian function for P mThe first and second order derivatives of H1 and H3 are uncertain because of the positive and negative coefficients of the first order terms, which leads to uncertainty in the calculation of the minimum value of the Hamiltonian function. Therefore, we need to find the value of H1 and H3 with respect to P. m The first and second derivatives of are shown in formula (7).

[0023]

[0024] From formula (7), we can know that when When , the first-order derivatives of H1 and H3 are both less than 0, showing a downward trend; when When , the first-order derivative of H1 is greater than 0, and the first-order derivative of H3 is less than 0, and the change trends are opposite; when When the first-order derivatives of H1 and H3 are both greater than 0, they show an upward trend and Therefore, the minimum expression of the Hamiltonian function of the reversible motor power is shown in formula (8).

[0025]

[0026] 3. Determine the dynamic switching conditions of the operating mode based on the Hamiltonian function of the reversible motor power and determine the final control variable reversible motor power P m And the engine power P eng Optimal working value:

[0027] According to Hamiltonian function (6), H2 and H4 are related to the reversible motor power P m H1 and H3 are both quadratic functions of motor power, P m The minimum value can be obtained by taking the first-order derivative of the Hamiltonian function, as shown in formula (9).

[0028]

[0029] Substituting formula (9) into formula (6) and combining it with formula (8) we can obtain the dynamic switching condition as follows:

[0030] when hour, H4 takes the minimum value, otherwise H1 takes the minimum value.

[0031] when hour, H4 takes the minimum value, otherwise H2 takes the minimum value.

[0032] when hour, H4 takes the minimum value, otherwise H3 takes the minimum value.

[0033] The reversible motor efficiency η under the above switching conditions m, engine thermal efficiency e, coordination factor s and engine friction loss power P eng,loss It is not a constant, so the switching conditions formulated by the Hatch density function will change with the change of the operating state of the hybrid power system, overcoming the defect of the traditional rule-based method to artificially determine the boundary conditions.

[0034] In summary, combining equations (6)-(8) and the above dynamic switching conditions, the final control variable reversible motor power P can be obtained: m And the engine power P eng The best working value is:

[0035]

[0036] P eng =P ref -P m (11)

[0037] The beneficial effect of the present application is that: the present application fully considers the key factor that the working change of the power source may induce the change of the switching condition. In order to solve the problem of poor distribution effect caused by fixed switching conditions, the Pontryagin Minimum Principle (PMP) is introduced to optimize the switching conditions in real time, thereby improving the overall operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific implementation of the present invention or the technical solution in the prior art, the following briefly introduces the drawings required for use in the specific implementation or the description of the prior art.

[0039] Figure 1 A block diagram of an amphibious vehicle provided for one embodiment of the present invention;

[0040] Figure 2 A flow chart of a method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization provided in one embodiment of the present invention;

[0041] Figure 3 These are the four working modes of the present invention;

[0042] Figure 4 For the present invention The changing trend of Hamiltonian function curve;

[0043] Figure 5 For the present invention The changing trend of Hamiltonian function curve;

[0044] Figure 6 For the present invention The changing trend of Hamiltonian function curve;

[0045] Figure 7It is a torque (power) distribution diagram in an implementation case of the present invention;

[0046] Figure 8 It is a working mode distribution diagram in the real-time case of the present invention.

[0047] Marking Description:

[0048] 101-driving motor; 102 controller; 103-natural gas engine; 104-transmission;

[0049] 105- reversible motor; 106- battery pack; 107- propeller. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the technical solution of the present application, the present invention is further described in detail below in conjunction with the accompanying drawings and the best embodiment.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0052] Reference Figure 1-5 , which is an embodiment of the present invention, provides a PMP optimized amphibious hybrid power distribution method for navigation, comprising:

[0053] S101: Constructing the power source output power relationship of the amphibious hybrid power system;

[0054] Build required power P ref With engine power P eng , reversible motor power P m The relationship is shown in formula (1).

[0055] P eng =P ref -P m (1)

[0056] Build battery power P bat With reversible motor power P m The relationship is shown in equations (2)-(3).

[0057]

[0058] Where P ref is the required power, P eng is the engine power, P m is the reversible motor power, P bat is the battery power, η m is the working efficiency of the reversible motor, P bat,loss To consume power for the battery, Where V oc is the open circuit voltage of the battery, and R is the internal resistance of the battery.

[0059] Build engine power P eng With fuel release power P fuel The relationship between them is shown in formula (4).

[0060]

[0061] Where P fuel Power released for fuel, P eng,loss is the friction loss power of the engine, and e is the thermal efficiency of the engine.

[0062] S102: Based on the PMP theory, construct the Hamiltonian function of the reversible motor power; as shown in formula (5).

[0063]

[0064] Where H(P m ) is the reversible motor power P m Hamiltonian function, δ is the engine working state, and s is the dynamic coordination factor.

[0065] When the amphibious hybrid vehicle is in navigation state, it can be divided into hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode according to the participation of the power source. Figure 3 shown.

[0066] According to the Hamiltonian function of formula (5), the Hamiltonian expression under different working modes can be derived as shown in formula (6).

[0067]

[0068] Where H 1，2,3,4 They represent the Hamiltonian function of the hybrid power system when it works in hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode. In order to find the minimum control P of the Hamiltonian function (Equation (6)), m , we need to further analyze the Hamiltonian function for P m The first and second order derivatives of . The positive and negative coefficients of the first order terms of H1 and H3 are uncertain, which leads to uncertainty in the calculation of the minimum value of the Hamiltonian function. Therefore, we need to find the value of P for H1 and H3. m The first and second derivatives of are shown in formula (7).

[0069]

[0070] From formula (7), we can know that when When , the first-order derivatives of H1 and H3 are both less than 0, showing a downward trend; when When , the first-order derivative of H1 is greater than 0, and the first-order derivative of H3 is less than 0, and the change trends are opposite; when When the first-order derivatives of H1 and H3 are both greater than 0, they show an upward trend and In order to analyze more vividly where the minimum value of the Hamiltonian function is obtained, the as well as When , the general change trend of the Hamiltonian function curve is as follows: Figure 4-6 shown.

[0071] Therefore, the minimum expression of the Hamiltonian function of the reversible motor power is shown in formula (8).

[0072]

[0073] S103: Determine the dynamic switching condition of the operation mode based on the Hamiltonian function of the reversible motor power, and determine the final control variable reversible motor power P m And the engine power P eng The best working value of

[0074] According to Hamiltonian function (6), H2 and H4 are related to the reversible motor power P m H1 and H3 are both quadratic functions of motor power, P m The minimum value can be obtained by taking the first-order derivative of the Hamiltonian function, as shown in formula (9).

[0075]

[0076] Substituting formula (9) into formula (6) and combining it with formula (8) we can obtain the dynamic switching condition as follows:

[0077] when hour, H4 takes the minimum value, otherwise H1 takes the minimum value.

[0078] when hour, H4 takes the minimum value, otherwise H2 takes the minimum value.

[0079] when hour, H4 takes the minimum value, otherwise H3 takes the minimum value.

[0080] The reversible motor efficiency η under the above switching conditions m , engine thermal efficiency e, coordination factor s and engine friction loss power P eng,lossIt is not a constant, so the switching conditions formulated by the Hatch density function will change with the change of the operating state of the hybrid power system, overcoming the defect of the traditional rule-based method to artificially determine the boundary conditions.

[0081] In summary, combining equations (6)-(8) and the above dynamic switching conditions, the final control variable reversible motor power P can be obtained: m And the engine power P eng The best working value is:

[0082]

[0083] P eng =P ref -P m (11)

[0084] S104: Output reversible motor power and engine power

[0085] The power distribution method of the amphibious hybrid vehicle optimized by PMP is used for simulation analysis. The fluctuation of power (torque) and working mode is shown in the figure. Figure 7-8 shown.

[0086] Obviously, the above embodiments are merely examples for clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from them are still within the protection scope of the invention.

Claims

1. A method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization, characterized in that: include: (1) Establish the power source output power relationship of the amphibious hybrid power system; (2) Based on the PMP theory, construct the Hamiltonian function of the reversible motor power; (3) Determine the dynamic switching conditions of the operating mode based on the Hamiltonian function of the reversible motor power and determine the final control variable reversible motor power P m And the engine power P eng The best working value.

2. The method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization according to claim 1 is characterized in that: The step (1) of establishing the output power relationship of the power source of the amphibious hybrid power system specifically includes: Build required power P ref With engine power P eng , reversible motor power P m relationship; Build battery power P bat With reversible motor power P m relationship; Build engine power P eng With fuel release power P fuel The relationship of existence.

3. The method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization according to claim 1 is characterized in that: When the amphibious hybrid power amphibious vehicle is in navigation state, the operation modes are divided into hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode according to the participation of the power source of the amphibious hybrid power system.

4. The method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization according to claim 1 is characterized in that: In the step (2), based on the PMP theory, a Hamiltonian function of the reversible motor power is constructed, which specifically includes: According to the PMP theory, a Hamiltonian function of the reversible motor power is constructed, and the Hamiltonian function of the reversible motor power is as follows: Where H(P m ) is the reversible motor power P m The Hamiltonian function, P ref is the required power, P m is the reversible motor power, η m is the working efficiency of the reversible motor, δ is the working state of the engine, s is the dynamic coordination factor, P eng,loss is the engine friction loss power, e is the engine thermal efficiency, Where V oc is the open circuit voltage of the battery, and R is the internal resistance of the battery; The Hamiltonian expressions of the hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode are derived based on the Hamiltonian function of the reversible motor power: Where H 1，2,3,4 They represent the Hamiltonian functions of the hybrid power system when it works in hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode respectively.

5. The method for allocating navigation power of a hybrid amphibious vehicle based on PMP optimization according to claim 1 is characterized in that: Combining the Hamiltonian expressions and dynamic switching conditions of the hybrid propulsion mode, mechanical propulsion mode, mechanical charging propulsion mode and electric propulsion mode, the final control variable reversible motor power P is obtained. m And the engine power P eng The best working value is:

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