US 12,125,324 B1 · Configuration evaluation method and platform for electromechanical coupling transmission of hybrid electric vehicles

Abstract

A configuration evaluation method and a platform for electromechanical coupling transmission of hybrid electric vehicles, includes an energy flow transfer path evaluation module for evaluating the energy flow transfer path, an electromechanical coupling transmission dynamic performance evaluation module for evaluating the dynamic performance of electromechanical coupling transmission, an electromechanical coupling transmission economic efficiency evaluation module for evaluating the economic efficiency of electromechanical coupling transmission, an electromechanical coupling transmission driving cycle adaptability evaluation module for evaluating the driving cycle adaptability of electromechanical coupling transmission, a component feature parameter rationality evaluation module for evaluating the rationality of component feature parameters, a structure and cost evaluation module for evaluating the structure and cost, and a comprehensive evaluation module for performing a comprehensive evaluation.

A configuration evaluation method for electromechanical coupling transmission of hybrid electric vehicles, comprising:

step 1:
evaluating an energy flow transfer path:
determining an energy flow transfer path of a configuration to be evaluated, including a pure electric working mode, a series extend range working mode, a parallel charging mode, an engine direct driving mode, a parallel driving mode and a power split working mode;
performing kinematic and mechanical analysis on different energy flow transfer paths, determining a rotation speed and torque matching relationship between all components and the engine, driving motor and generator, and performing performance and risk assessments from the perspectives of kinematics and mechanics;
step 2:
evaluating the dynamic performance of electromechanical coupling transmission:
evaluating the dynamic performances corresponding to different working modes determined in step 1, comprising calculating the acceleration time under an independent working mode and a joint working mode of the engine and driving motor, as well as the maximum climbing degree and the maximum speed that can be reached;
step 3:
evaluating the economic efficiency of electromechanical coupling transmission:
constructing a global optimal energy management strategy to evaluate the energy consumption of the electromechanical coupling transmission, and testing the energy consumption of the electromechanical coupling transmission in a balanced state maintained by the battery SoC, the energy consumption from the SoC maximum limit state to the minimum limit state, and the energy consumption in a power shortage state, thereby calculating the fuel consumption and power consumption per hundred kilometers of the electromechanical coupling transmission, the pure electric endurance mileage, the operating high-efficiency area ratio of the engine, driving motor and generator, as well as the carbon emission data, and predicting an energy consumption cost in each year of travel;
step 4:
evaluating the driving cycle adaptability of electromechanical coupling transmission:
further analyzing based on the results calculated by the global optimal energy management strategy in step 3, including the number of switching times of the working modes, the number of engine's startup times, the distribution utilization ratio of operation modes, the brake energy recovery degree, and the number of times of charging and discharging;
step 5:
evaluating the rationality of component feature parameters:
introducing different vehicle model parameters, and evaluating whether the electromechanical coupling transmission matches the target vehicle model;
introducing all the feature parameters, performing matching checks, proofreading and rationality evaluation on the feature parameters of different components, and performing rationality evaluation on the design scope of different feature parameters;
step 6:
evaluating the structure and cost:
evaluating the structure of the electromechanical coupling transmission determined in step 5, including the structural complexity, compactness and enveloping space;
evaluating the weight and cost of the electromechanical coupling transmission, including the total weight/cost and item weight/cost;
step 7:
performing a comprehensive evaluation:
taking into account the evaluation of energy flow transfer path of the electromechanical coupling transmission, the evaluation of dynamic performance, the evaluation of economic efficiency, the evaluation of driving cycle adaptability, the evaluation of rationality of component feature parameters and the evaluation of structure and cost in steps 1-6, performing a comprehensive evaluation on the effective electromechanical coupling transmission evaluation object determined in step 5, and performing a key optimization on the electromechanical coupling transmission indicators according to the target requirements of product design;
step 3 further comprising:
step 31:
constructing a global optimal energy management strategy:
first, determining a target driving cycle, and selecting different driving cycles for adaptive combination, wherein each moment corresponds to a state variable xt and a control variable ut, ft(xt,ut) indicates that there is a unique corresponding relationship between the state variable and the control variable, wherein as shown in formula (3-1), the state variable xt comprises a battery SoC working mode and an electromechanical coupling transmission working mode, and the control variable ut comprises the rotation speed and torque of the engine, as well as the rotation speed and the torque of the driving motor;
second, determining an optimal control sequence u* of an accumulated objective function J by using a time reversal method, as shown in formula (3-2), calculating and storing a corresponding instantaneous cost function Γt after combining all state variables and control variables within each time step length, calculating an accumulated cost value, and determining an optimal control sequence by minimizing the accumulated cost, wherein the references of the accumulated objective function in this step are set ideal values of the minimum fuel consumption and the battery SoC target value, and subsequently, a multi-objective optimization may be performed according to the feedback of the evaluation indicators;
finally, performing a forward operation under a target driving cycle using the optimal control sequence, thereby obtaining an instantaneous fuel consumption and power consumption of the electromechanical coupling transmission at each moment, and subsequently, obtaining the hundred-kilometer fuel consumption QT according to the total fuel consumption mT and the accumulated driving mileage S corresponding to the operating condition, as shown in formula (3-3),
x
t
+
1
=
f
t
(
x
t
,
u
t
)
(
3
⁢
‐
⁢
1
)
J
⁡
(
x
0
)
=
min
u
J
⁡
(
x
0
,
u
*
)
=
Γ
t
(
x
t
)
+
∑
t
=
1
t
-
1
Γ
t
(
x
t
,
u
t
)
(
3
⁢
‐
⁢
2
)
Q
T
=
m
T
1000
⁢
ρ
⁢
S
×
1
⁢
0
⁢
0
(
3
⁢
‐
⁢
3
)
wherein t represents a time step length of the target operating condition, J(x0) represents an accumulated objective function corresponding to the optimal control sequence u* starting from an initial condition x0, Γ represents an instantaneous cost function, wherein the corresponding optimal control sequence is solved when the accumulated objective function is minimized, wherein ρ represents the gasoline density, and S represents the accumulated mileage of travel;
step 32:
performing an energy consumption test by respectively giving an initial state value and a final state value of the SoC, wherein the initial value and the final value of the SoC set in a balanced state maintained by the battery SoC are usually set to be 0.5, wherein for the energy consumption from the SoC maximum limit value state to the minimum limit value state, the initial value and the final value of the SoC are usually set to be 0.7 and 0.3, wherein for the power consumption in a power shortage state, the initial value and the final value of the SoC are both set to be 0.3;
step 33:
after the target driving cycle is given, setting the initial value of the battery SoC to be the maximum limit value state, and making the operating condition cycle using only the pure electric working mode until the final state of the SoC reaches the minimum limit state, and subsequently, respectively recording the pure electric endurance mileages E34_1, E34_2, E34_3 and E34_4 of the electromechanical coupling transmission under different driving cycles including standard, urban, suburban and high-speed driving cycle, wherein the sum of the operating condition weights α34_1, α34_2, α34_3 and α34_4 is 1, and the weights may be adaptively adjusted according to the design requirements, thereby obtaining an accumulated mileage by final weighting, namely, the pure electric endurance mileage E34, as shown in formula (3-4):
E34=α34_1E34_1+α34_2E34_2+α34_3E34_3+α34_4E34_4 (3-4);
step 34:
calculating the proportions of high efficiency operation areas of the engine, the driving motor and the generator:
as shown in formula (3-5);
reading the rotation speeds and torques of the engine, the driving motor and the generator in the optimal control sequence in step 31, drawing operating points on an efficiency map corresponding to the engine, the driving motor and the generator, counting the operating points of the engine in the top 20% percentile of the highest and lowest efficiency areas, and using it as the proportion E35_1 of high efficiency operation area of the engine;
similarly, counting the operating points of the driving motor and the generator in the top 20% percentile of the highest and lowest efficiency areas, and using them as the proportions E35_2 and E35_3 of high efficiency operation areas of the driving motor and the generator,
E35_f=find(Mapf(nf,Tf)(0-20%)) (3-5)
wherein f=1, 2, 3 represents different power sources, including the engine, the driving motor and the generator, nf represents rotation speeds corresponding to different power sources, and Tf represents torques corresponding to different power sources;
step 35:
calculating the carbon emission data E36:
according to the hundred-kilometer fuel consumptions E31_1, E32_1, and E33_1 under three different battery SoC state scenarios obtained in step 31, and the sum of the weights α36_1, α36_2, and α36_3 of the three scenarios corresponding to the operating conditions is 1, adaptively adjusting the weights based on the design requirements, and by multiplying with the carbon emission coefficient Kco2 per liter of gasoline and the estimated annual mileage of travel, thereby obtaining the carbon emission data of the target vehicle model, as shown in formula (3-6):
E
3
⁢
6
=
1
1
⁢
0
⁢
0
×
(
α
36
⁢
_
⁢
1
⁢
E
31
⁢
_
⁢
1
+
α
36
⁢
_
⁢
2
⁢
E
32
⁢
_
⁢
1
+
α
36
⁢
_
⁢
3
⁢
E
33
⁢
_
⁢
1
)
×
K
c
⁢
o
⁢
2
(
3
⁢
‐
⁢
6
)
step 36:
predicting the energy consumption cost E37 in each year of travel, including the fuel consumption cost and power consumption cost:
according to the hundred-kilometer fuel consumptions E31_1, E32_1, and E33_1 under three different battery SoC state scenarios obtained in step 31, and the sum of the weights α37_1, α37_2, and α37_3 of the three scenarios corresponding to the operating conditions is 1, adaptively adjusting the weights based on the design requirements, and by multiplying with the cost price per liter of gasoline Pfuel and the estimated annual mileage of travel Stravel, thereby obtaining the fuel consumption cost E37_1, as shown in formula (3-7), wherein similarly, according to the power consumptions corresponding to E31_2, E32_2 and E33_2, and the sum of the weights α37_1, α37_2, and α37_3 of the three scenarios corresponding to the operating conditions is 1, adaptively adjusting the weights based on design requirements, and by multiplying with the cost price per kWh of electricity PBat with the estimated annual mileage of travel Stravel, thereby obtaining the power consumption cost E37_2, as shown in formula (3-8), wherein the total energy consumption cost is shown in (3-9):
E
37
⁢
_
⁢
1
=
1
1
⁢
0
⁢
0
×
(
α
37
⁢
_
⁢
1
⁢
E
31
⁢
_
⁢
1
+
α
37
⁢
_
⁢
2
⁢
E
32
⁢
_
⁢
1
+
α
37
⁢
_
⁢
3
⁢
E
33
⁢
_
⁢
1
)
×
P
fuel
×
S
travel
(
3
⁢
‐
⁢
7
)
E
37
⁢
_
⁢
2
=
1
1
⁢
0
⁢
0
×
(
α
37
⁢
_
⁢
1
⁢
E
31
⁢
_
⁢
2
+
α
37
⁢
_
⁢
2
⁢
E
32
⁢
_
⁢
2
+
α
37
⁢
_
⁢
3
⁢
E
33
⁢
_
⁢
2
)
×
P
Bat
×
S
travel
(
3
⁢
‐
⁢
8
)
E
37
=
E
37
⁢
_
⁢
1
+
E
37
⁢
_
⁢
2
(
3
⁢
‐
⁢
9
)
step 4 further comprising:
step 41:
calculating the number of switching times of working modes E41:
reading the working mode corresponding to each moment calculated by the global optimal energy management strategy in step 31, calculating the working modes of adjacent moments using a difference value method, wherein a zero difference indicates a same working mode, and a non-zero difference indicates different working modes;
counting and recording the number of times the non-zero difference appears, which is the number of switching times of working modes of the electromechanical coupling transmission under corresponding operating conditions, as shown in formula (4-1);
similarly, recording the number of switching times of working modes E41_1, E41_2, E41_3 and E41_4 under different operating conditions including standard, urban, suburban and high-speed driving cycle,
E
4
⁢
1
=
{
Sum
=
Sum
⁢
+
0
⁢
if
⁢
Mode
(
t
+
1
)
-
Mode
(
t
)
==
0
Sum
=
Sum
⁢
+
1
⁢
if
⁢
Mode
(
t
+
1
)
-
Mode
(
t
)
∼
=
0
(
4
⁢
‐
⁢
1
)
wherein Mode_s(t) represents the working mode at the moment t, and Mode_s(t+1) represents the working mode at the moment t+1;
step 42:
calculating the number of the engine's startup times E42:
reading the working mode corresponding to each moment calculated by the global optimal energy management strategy in step 31, marking the working mode with the participation of engine as 1 and the working mode without the participation of engine as 0, and calculating the working modes of adjacent moments using a difference value method, wherein when the difference is 0, it indicates a same working mode, and when the difference is 1, it indicates the engine's startup state;
subsequently, counting and recording the number of times that the difference is 1 appears, which is the number of engine's startup times of the electromechanical coupling transmission under corresponding operating conditions, as shown in formula (4-2);
similarly, recording the number of engine's startup times E42_1, E42_2, E42_3 and E42_4 under different operating conditions (standard, urban, suburban and high-speed driving cycle),
E
42
=
{
Sum
=
Sum
+
0
⁢
if
⁢
ICE
(
t
+
1
)
-
ICE
(
t
)
==
0
Sum
=
Sum
+
1
⁢
if
⁢
ICE
(
t
+
1
)
-
ICE
(
t
)
⁢
=
=
⁢
1
,
(
4
⁢
‐
⁢
2
)
wherein ICE(t) represents the engine's startup state at the moment t, and ICE(t+1) represents the engine's startup state at the moment t+1;
step 43:
calculating the proportion of distribution and utilization of working modes E43:
reading the working mode corresponding to each moment calculated by the global optimal energy management strategy in step 31, wherein different working modes have different marked states;
subsequently, counting the number of times that different working modes appear, and recording the proportion of distribution of different working modes by comparing with the total number of times that the working modes appear, as shown in formula (4-3);
similarly, recording the proportion of distribution of working modes under different operating conditions including standard, urban, suburban and high-speed driving cycle;
E
43
⁢
_
⁢
y
=
Mode
(
y
)
Mode
⁡
(
Total
)
(
4
⁢
‐
⁢
3
)
wherein y represents different states of working modes, Mode(y) represents the number of times that different working modes appear, and Mode(Total) represents the total number of times that the working modes appear;
step 44:
evaluating the degree of brake energy recovery and utilization E44 in step 4;
reading the time segment corresponding to the brake recovery working mode calculated by the global optimal energy management strategy in step 31, and statistically analyzing the energy recovery power Pr in the time segment of brake recovery, as shown in formula (4-4);
meanwhile, statistically analyzing and summing up the brake energy recovery power in different time segments under the target operating condition;
further, performing a proportion analysis of the total power PT consumed under the target operating condition, as shown in formula (4-5), thereby determining the degree of energy recovery and utilization in the time segment of the target operating condition,
P
r
=
∫
t
⁢
1
⁢
0
t
⁢
1
⁢
1
T
M
⁢
o
⁢
t
×
n
M
⁢
o
⁢
t
×
η
M
⁢
o
⁢
t
/
9550
(
4
⁢
‐
⁢
4
)
E
4
⁢
4
=
∑
t
⁢
o
⁢
t
⁢
a
⁢
l
⁢
P
r
P
T
(
4
⁢
‐
⁢
5
)
wherein TMot represents the torque of the driving motor, nMot represents the speed of the driving motor, ηMot represents the mechanical efficiency of the driving motor at the corresponding speed and torque, t10 represents the starting segment of brake energy recovery, t11 represents the ending segment of brake energy recovery, and E44 represents the ratio of brake energy recovery power to total power;
step 45:
calculating the number of charging and discharging times E45_1, distribution range of charging/discharging duration E45_2, and number of switching times of charging and discharging E45_3;
reading the working mode corresponding to each moment calculated by the global optimal energy management strategy in step 31, wherein different working modes have different marked states;
subsequently, marking the charging state working modes as 10, marking the discharging state working mode as 20, and marking the non-discharging working mode as 0;
counting the number of times E45_1_charge/E45_1_discharge corresponding to the charging/discharging state working modes, and calculating the distribution range of each charging/discharging duration E45_2_charge/E45_2_discharge;
in addition, calculating the charging/discharging state of adjacent moments using a difference value method, wherein a zero difference indicates a same state, and a non-zero difference indicates a switching between charging and discharging;
counting and recording the number of times that a non-zero difference appears, which is the number of switching times of charging and discharging under the corresponding operating conditions of the electromechanical coupling transmission, as shown in formula (4-6),
E
45
⁢
_
⁢
3
=
{
Sum
=
Sum
+
0
⁢
if
⁢
Bat
(
t
+
1
)
-
Bat
(
t
)
==
0
Sum
=
Sum
+
1
⁢
if
⁢
Bat
(
t
+
1
)
-
Bat
(
t
)
∼
=
0
(
4
⁢
‐
⁢
6
)
wherein Bat(t) represents a battery charging/discharging state at the moment t, and Bat(t+1) represents a battery charging/discharging state at the moment t+1.

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Configuration evaluation method and platform for electromechanical coupling transmission of hybrid electric vehicles

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Configuration evaluation method and platform for electromechanical coupling transmission of hybrid electric vehicles

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Abstract

Claims14