CN202498998U - Fuel cell hybrid energy management control system - Google Patents

Abstract

The utility model discloses a fuel cell hybrid energy management control system, which includes a fuel cell, a fuel cell controller, a DC/DC converter, a lithium battery, a vehicle controller, a motor controller, and a motor, and is characterized in that: The fuel cell and the lithium battery are connected to the busbar of the power system through a DC/DC converter and are controlled by the motor controller to be the output power of the motor. The fuel cell is controlled by the fuel cell controller, and the fuel cell The battery controller, DC/DC converter, lithium battery, and motor controller are controlled by the vehicle controller. The controller makes the efficiency of the whole vehicle more than 50%, improves the fuel economy of the whole vehicle and at the same time makes the fuel cell and lithium battery work in the best state.

Description

Fuel cell hybrid energy management control system

technical field

The utility model belongs to an energy management control system, in particular to a fuel cell hybrid power energy management control system.

Background technique

The energy management strategy of the hybrid power system of fuel cell vehicles is one of the key technologies in the research of fuel cell power systems. Its core is to reduce the dynamic load of the fuel cell engine and optimize the work of the fuel cell engine by allocating the energy output of the fuel cell and auxiliary energy in real time. area and maximize the recovery of braking energy to optimize the efficiency of the power system.

Utility model content

The purpose of the utility model is to provide a fuel cell hybrid power energy management control system, which can make the efficiency of the whole vehicle reach more than 50%, improve the fuel economy of the whole vehicle and make the fuel cell and lithium battery work in the best state.

In order to achieve the above purpose, the fuel cell hybrid energy management control system of the present invention includes a fuel cell, a fuel cell controller, a DC/DC converter, a lithium battery, a vehicle controller, a motor controller, and a motor, and is characterized in that: The fuel cell and the lithium battery are connected to the busbar of the power system through a DC/DC converter and are controlled by the motor controller to be the output power of the motor. The fuel cell is controlled by the fuel cell controller, and the fuel cell The battery controller, DC/DC converter, lithium battery, and motor controller are controlled by the vehicle controller.

Specifically: the vehicle controller includes an energy controller and a fuzzy controller, the energy controller is controlled by the fuzzy controller, and the fuel cell, DC/DC converter, and lithium battery are controlled by the energy control The lithium battery outputs power to the motor through a fuzzy controller, an energy controller, and a motor controller, and the actual power of the motor is fed back to the energy controller. The fuel cell and the lithium battery input power to the motor through the energy switching module and the driving interface, and the power switching module and the driving interface are controlled by the motor controller.

The beneficial effects of the utility model are: the management control system can optimize the energy management strategy of the whole vehicle according to the characteristics of the fuel cell hybrid power system, and the state of charge SOC of the lithium battery and the required power P of the whole vehicle are input variables, and the fuel cell Provide power, provide power from lithium batteries, and recover braking energy as output variables. Propose a real-time energy control algorithm for hybrid power systems based on fuzzy control, perform simulation and implement the algorithm on the hardware platform, and simulate the algorithm and load the controller on the road of the sample vehicle The driving test results show that the control system makes the efficiency of the whole vehicle more than 50%, improves the fuel economy of the whole vehicle, and at the same time makes the fuel cell and lithium battery work in the best state.

Description of drawings

Fig. 1 is a block diagram of the fuel cell hybrid power system of the present invention, in which the solid line represents the control flow, and the dotted line represents the energy flow;

Fig. 2 is the measured fuel cell efficiency curve;

Fig. 3 is a block diagram of fuel cell hybrid energy management control, in which the solid line represents the control flow, and the dotted line represents the energy flow;

Fig. 4 is the membership degree function graph of power error signal _Pg ;

Fig. 5 is a membership function graph of the SOC of the state of charge of the lithium battery;

Fig. 6 is the membership function graph of the power P _b provided by the lithium battery;

Fig. 7 is a curve diagram of the membership function of the fuel cell output power Pfc;

Fig. 8 is a fuzzy controller input and output waveform diagram;

Fig. 9 is a block diagram of the circuit implementation of the motor control system, in which the solid line represents the control flow, and the dotted line represents the energy flow.

Detailed ways

Below in conjunction with accompanying drawing, the utility model is further described.

The fuel cell hybrid energy management control system of the present utility model, as shown in Figures 1, 3, and 9, includes a fuel cell, a fuel cell controller, a DC/DC converter, a lithium battery, a vehicle controller, and a motor controller , motor, fuel cell, and lithium battery are connected to the busbar of the power system through a DC/DC converter and controlled by the motor controller as the output power of the motor. The fuel cell is controlled by the fuel cell controller, fuel cell controller, and DC/DC converter , lithium battery, and motor controller are controlled by the vehicle controller.

Specifically, the vehicle controller includes an energy controller and a fuzzy controller (see Figure 3), the energy controller is controlled by the fuzzy controller, the fuel cell, DC/DC converter, and lithium battery are controlled by the energy controller, and the lithium The battery outputs power to the motor through the fuzzy controller, energy controller, and motor controller, and the actual power of the motor is fed back to the energy controller. The fuel cell and lithium battery input power to the motor through the energy switching module and the driving interface (see Figure 9), and the power switching module and the driving interface are controlled by the motor controller.

The power system of a fuel cell hybrid electric vehicle is a multi-energy powertrain system. Its structure is shown in Figure 1. It adopts a structure in which fuel cells, auxiliary batteries (lithium batteries) and braking energy recovery are mixed configurations of three energy sources. . During the driving process, the fuel cell is used as the main energy source to provide the power required to drive the electric vehicle. Due to the soft dynamic characteristics of the fuel cell, it cannot provide high power for instant start, acceleration, and climbing. It is necessary to configure an auxiliary battery. It also absorbs excess power from fuel cells and recovers braking energy. According to a certain control strategy, the vehicle control system reasonably optimizes the distribution of the output or input power of the three, so as to obtain higher fuel economy on the basis of satisfying the power performance of the vehicle.

As shown in Figure 1, each component forms a distributed control system through the CAN bus. The electric power generated by the 5KW fuel cell is transformed into a stable 60V DC voltage through the main DC/DC converter and transmitted to the power system bus. The 60HA lithium battery is directly connected to the busbar through DC/DC, and the power is directly transmitted to the busbar. Power for the AC motor and its controller is provided by the powertrain bus. The bus power p _bus is as follows:

p _bus ＝(P _fc +P _d )η _d

${\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; the\; bus</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}}}{{\mathrm{<span\; class="notranslate">\; \&eta;</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}}}$

∴p _g ＝(P _fc +P _f )η _d η _m

In the formula, p _b is the battery power; p _fc is the fuel cell output power; p _bus is the power output from the main DC/DC converter to the bus; p _g is the driver's demand power (driving power on the wheels); η _fc , η _d , η _m fuel cell efficiency, DC/DC converter efficiency, and motor and transmission efficiency.

Start\acceleration\climbing mode: Lithium battery is the main energy flow, and the fuel cell works in a constant power state;

Cruise mode: the fuel cell engine is the main energy flow, and the lithium battery is the auxiliary energy flow;

In light-load operation mode: the fuel cell engine charges the lithium battery while providing the required energy to the motor;

In deceleration/braking mode, the lithium battery recovers regenerative braking energy.

According to their different working modes, the specific shares of the two power supplies to the load are different. The general principle of the ratio is: to keep the fuel cell in the best state, and at the same time make the lithium battery state of charge above SOCmin. The output power of the lithium battery is adjusted with the power share allocated to the fuel cell as a constraint. For the battery, when the battery SOC minimum limit value (SOCmin) is less than or equal to 30%, the battery must be charged; when the SOC is 50% to 70%, it can be charged or discharged depending on the total power demand of the vehicle; when the SOC is greater than Not charging at 90%.

This paper uses the fuel cell efficiency diagram (see Figure 2) as a fuel cell working model. The power range of fuel cell is low power range from 0-0.5kW, and the efficiency of fuel cell is the highest at this time. When the fuel cell is running at moderate demand power (1-3kW), any excess power can be used to charge the battery. When the required power is high (3-5kW), the fuel cell is not used to charge the battery.

During real road driving, the driver controls the accelerator pedal and brake pedal according to road traffic conditions, vehicle dynamic performance and his own driving habits. The energy management control system of a hybrid electric vehicle first needs to interpret the position of the accelerator pedal or brake pedal at the current vehicle speed as the driver's desired power (that is, the driver's demanded power), and then distribute the driver's demanded power to the driver through the energy management strategy. Fuel cell system and storage battery are two energy sources to achieve the best energy efficiency. When braking or coasting, the expected power is negative for braking energy recovery. As shown in Figure 3.

The fuzzy controller takes the target power P _g and the state of charge SOC of the lithium battery as the input variables of the fuzzy control, and takes the fuel cell distribution output power P _fc , the lithium battery output power P _b and the braking energy recovery power Pr as the fuzzy controller output variable. The fuzzy input variable P _g and the basic domain of SOC are [-9, 9]KW and [30, 90]%, the input variable is fuzzy, and the fuzzy subset is {NB (negative large), NM (negative medium), NS (negative small), ZO (zero), PS (positive small), PM (positive middle), PB (positive large)}; the domain of fuzzy output variable Pb is [-3, 6]KW, and the fuzzy subset is also {NB (Negative Large), NM (Negative Middle), NS (Negative Small), ZO (Zero), PS (Positive Small), PM (Positive Middle), PB (Positive Big)}, the domain of the fuzzy output variable P _fc is [0 , 3] KW, the fuzzy subset is also {ZO (zero), PS (positive small), PM (positive middle), PB (positive big)}, the domain of fuzzy output variable P _r is [0, 3] KW, fuzzy The subsets are also {ZO (zero), PS (positive small), PM (positive middle), PB (positive big)}. Select the membership function of the input and output fuzzy variables as a triangle, as shown in Figure 4-7.

The fuzzy control rules are connected by a series of relational words. The most commonly used relational words are if-then, also, or and and. The fuzzy control rules for determining each output and input are shown in Table 1. The control amount given by the fuzzy control algorithm cannot directly control the object, and the actual output needs to be defuzzified to convert it into the basic domain acceptable to the control object. The defuzzification algorithm uses the centroid method.

Table 1 Fuzzy control rule table

A fuzzy controller is established in the Matlab simulation system, and the input variables of the fuzzy control target power P _g and the state of charge SOC of the lithium battery are [-9, 9] KW and [30, 90] %, and the fuzzy control The output variables of the fuel cell distribution output power P _fc , lithium battery distribution output power P _b and braking energy recovery power P _r are respectively [0, 5] KW, [-3, 6] KW and [0, 3] KW. The lithium battery is 60AH/48V, and the initial state of charge of the battery is SOC=60%. At the same time, in the Matlab/Simulink environment, a BLCDM control system simulation model is established. The motor parameters are: rated power 5kW, rated speed 1500r/min, rated input voltage 48V, rated current 85A, stator resistance = 0.2Ω, moment of inertia = 0.05kg m2, Rated torque Te = 80Nm. Convert the driver's accelerator pedal and brake pedal into the target power, and take the time 0-15 minutes to simulate the waveform as shown in Figure 8.

It can be seen from the simulation waveform that the fuzzy algorithm is used to dynamically manage the fuel cell output power, lithium battery output power and braking energy recovery power. During the entire working period, the SOC of the lithium battery is always between 30% and 70%. At any time, braking energy recovery is performed at any time, and the instantaneous maximum output power is within the allowable range of the lithium battery, and the lithium battery works at its best. The output power of the fuel cell is maintained between 1KW-3KW, which is the high-efficiency zone of the working fuel cell.

As shown in Figure 9, the motor controller CPU adopts the c8051 microprocessor, which mainly completes the acquisition of accelerator pedal information, brake signals, and motor position signals, converts the collected information into target power, and controls the fuel cell power, lithium battery and Control information for braking energy recovery, simultaneous motor speed control, and protection functions such as overcurrent, overvoltage and temperature.

The system of the utility model can perform global optimization based on the composition of different fuel cell hybrid power systems and the characteristics of energy flow, according to the electric vehicle cycle conditions and actual operating power test data, and analyze the fuel cells under different battery states of charge (SOC). Based on the law of output power target power change, a real-time control algorithm based on fuzzy logic was designed, and the algorithm was implemented on the DSP320TM2812 hardware platform, and a fuel cell vehicle controller was launched, which passed the actual operation test of a 5KW fuel cell tour bus It shows that the efficiency of the whole vehicle can reach more than 50%, which improves the fuel economy of the whole vehicle and makes the fuel cell and lithium battery work in the best state.

Claims (3)

1. fuel cell hybrid energy management control system; It comprises fuel cell, fuel cell controller, DC/DC conv, lithium cell, entire car controller, electric machine controller, motor; It is characterized in that: described fuel cell, lithium cell are connected with the power system bus and are the motor horsepower output by motor controller controls through DC/DC conv; Described fuel cell is controlled by described fuel cell controller, and described fuel cell controller, DC/DC conv, lithium cell, electric machine controller are controlled by entire car controller.

2. fuel cell hybrid energy management control system according to claim 1; It is characterized in that: said entire car controller comprises energy controller and fuzzy controller; Described energy controller is controlled by fuzzy controller; Described fuel cell, DC/DC conv, lithium cell are controlled by energy controller, and described lithium cell is the motor horsepower output through fuzzy controller, energy controller, electric machine controller, and the effect horse power of said motor feeds back to described energy controller.

3. fuel cell hybrid energy management control system according to claim 1; It is characterized in that: described fuel cell, lithium cell are power input to machine through energy switching module, driving interface, and described amount handover module, driving interface are controlled by described electric machine controller.

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