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The braking process of electric locomotive is featured by short braking time, large braking power, large voltage fluctuations, etc. Faced with the problem of low utilization of braking energy and high investment cost of the current regenerative braking energy utilization systems, an energy optimization scheme is proposed in this paper by combining the control strategy for energy storage and energy optimization. The regenerative braking energy utilization system is modeled by analyzing the braking process of electric locomotive. The instantaneous absorption reference powers of the energy storage subsystem and energy feedback subsystem in braking process are obtained according to the established mathematical model. The energy storage subsystem uses super capacitor and adopts a power-current dual closed-loop control strategy. The energy feedback subsystem adopts a voltage-current dual closed-loop control strategy. Through the tracking control of the instantaneous power, a reasonable distribution of the regenerative braking energy is achieved between the energy feedback subsystem and energy storage subsystem, thereby increasing the utilization efficiency of the two subsystems. Finally, the performance of the proposed scheme is verified by simulation and experiment.

Large amount of regenerative energy is generated in the process of electric locomotive braking. The effective recycling of regenerative energy has many benefits, e.g., stabilizing the bus voltage of traction network, preventing the failure of regenerative braking, and avoiding energy waste [

Currently, most of the existing electric locomotive braking systems adopt mechanical contracting brake or consume the regenerative energy on resistance [

The contribution of this paper mainly includes the following parts.

The rest of this paper is organized as follows. In Section

The energy storage subsystem consists of two components: the super capacitor bank for storing braking energy and the bidirectional DC-DC converter circuit for charging and discharging the super capacitor bank. The topology and working mode of this subsystem are shown in Figure _{2} is turned on with a certain duty cycle, constituting a boost chopper circuit with the antiparallel diode of VT_{1}. As a result, the energy is released to the bus of traction network, at which time_{L} is negative. When the electric locomotive is in braking state, the VT_{1} is turned on with a certain duty cycle, constituting a buck chopper circuit with the antiparallel diode of VT_{2} to absorb the feedback energy from the traction bus, at which time_{L} is positive.

Topology and working mode of bidirectional DC-DC converter.

Topology of super capacitor energy storage subsystem

Buck operation mode

Boost operation mode

According to the principle of PWM, we have

In steady state,

The dynamic equations for the inductor/capacitor branch are obtained by Kirchoff’s voltage law, as presented by

In (_{L} and the capacitor.

Therefore, the dynamics equation of the reduced-order model is obtained and described by

In this research, the energy storage subsystem adopts a dual loop control strategy where the traction bus voltage is the outer loop and the current is the inner loop. Figure

Control diagram of the energy storage subsystem.

The reference charging current

With a power electronics converter, the energy feedback subsystem gives back the braking energy to AC network. The energy feedback subsystem is mainly composed of isolating switch QF, feedback converter and isolated transformer, where the feedback converter is composed of power electronics module, control subsystem, and filter. The main circuit and control diagram of the energy feedback subsystem are shown in Figure

Main circuit and control diagram of the energy feedback subsystem.

Main circuit of the energy feedback subsystem

Control diagram of the energy feedback subsystem

To achieve the decoupled dual closed-loop control of the active and reactive current components in a simple way, the AC-side mathematical model after coordinate transformation is described by [

Thus, the control strategy of the current controller can be obtained by

Based on grid-voltage vector orientation, the voltage of AC network in (

There are generally two types of control strategies for the distribution of regenerative braking energy between the energy storage subsystem and the energy feedback subsystem, i.e., strategy of energy storage priority and strategy of energy feedback priority. For the purpose of reducing the capacity of the energy storage subsystem and improving the utilization efficiency of the energy feedback subsystem, the strategy of energy feedback priority is selected in this paper. The DC traction buses of the energy storage subsystem and the energy feedback subsystem are parallelly connected.

In the braking process, the speed of electric locomotive is reduced (or the S curve) with a constant deceleration. Figure _{1}, the electric locomotive enters the braking stage.

Energy distribution between energy feedback subsystem and energy storage subsystem.

It can be seen from Figure

To conduct the mathematical modeling, the first step is to obtain the relationship between braking time, initial braking speed, and braking torque by dynamics analysis.

The resistance in the process of electric locomotive braking is composed of basic resistance, electromagnetic braking resistance, and additional air braking resistance. The basic resistance includes bearing resistance, rolling resistance, sliding resistance, shock vibration resistance, and air resistance. The electromagnetic braking resistance is determined by the braking torque and some intrinsic parameters of the electric locomotive.

The basic resistance can be obtained by empirical experiment, which is

The electromagnetic braking resistance is given by

According to the basic law of dynamics, we have_{t} is the sum of all resistances in the braking process, _{b} is the electromagnetic braking resistance,

Therefore, the braking time of the electric locomotive can be expressed by

Bringing (_{s} is the speed of the electric locomotive when entering the braking stage and

For the convenience of modeling, the_{1} moment in the original coordinate system. In the new coordinate system, the feedback power in the braking process is given by

Then, the_{2} moment, i.e., the intersection of the feedback power curve and the maximum absorption power of the energy feedback system (the energy storage subsystem changes from absorbing power to releasing power), can be calculated by

Further, the energy absorbed by the energy storage subsystem and the energy absorbed by the energy feedback subsystem are calculated by

The super capacitors in the system require a large-scale combination of series and parallel work, and their overall performance will decrease depending on many factors such as temperature, bias voltage, and inconsistent monomer parameters [

To optimize the system, an objective function is defined as

When

To find the minimum of

Therefore, the maximum absorption power of the energy feedback subsystem is obtained as

Correspondingly, the instantaneous absorption power of the energy feedback subsystem and that of the energy storage subsystem can be obtained as

The control strategy in this research aims at controlling the feedback power of electric locomotive and the fluctuation in the DC bus voltage of traction network. This paper researches the master-slave control strategy combining energy storage and energy feedback. Specifically, the main controller distributes the absorption power of the energy storage subsystem and the energy feedback subsystem based on the DC bus voltage of traction network. The control diagram of the proposed energy distribution scheme is shown in Figure

Control diagram of the energy distribution scheme.

The energy storage subsystem adopts the dual closed-loop control strategy with active power and current. The reference power absorbed by the super capacitor can be obtained by (

In the braking stage, the distribution of feedback energy is as follows

To verify the effectiveness of the proposed energy distribution scheme, we let

To evaluate the effectiveness of the proposed energy distribution scheme and the control strategy, MATLAB/Simulink platform is used to construct the model of regenerative braking energy utilization system. Figure

Main circuit topology of hybrid braking energy utilization system in electric locomotive.

Tables

Parameters of electric locomotive system.

Parameter | Value |
---|---|

Model of traction motor | 1TB2010 |

Electric locomotive mass ( M/t) | 225 |

Rated power (P/MW) | 4.56 |

Max running speed (km/h) | 80 |

Rated voltage of traction network (U/V) | 1500 |

Wheel radius (R/m) | 0.4025 |

Motor efficiency | 0.9 |

Gearbox efficiency | 0.96 |

Max braking force (F/kN) | 342.24 |

Parameters of the super capacitor.

Parameter | Value |
---|---|

Single unit | 3000F, |

Energy density (Wh/kg) | 6 |

Combination of series and parallel connection | 4 parallel |

Available energy ( | 5.2 |

Max voltage (V) | 1250 |

The main parameters of the simulation model are as follows: DC bus voltage of traction network

Working characteristics of the energy storage subsystem.

Working characteristics of the energy feedback subsystem.

Energy cycling status during electric locomotive braking.

Working characteristics of the DC bus voltage.

Figure

Figure

Figure _{M}=8.1 _{L}=4.2

Figure

To verify the performance of the proposed scheme, the field experiment was carried out using the electric locomotive and other facilities from Zhuzhou CRRC Times Electric Co., Ltd. The parameters of the electric locomotive and the facilities are shown in Tables

Facilities for field experiment and the working characteristics of the electric locomotive.

Experiment system platform

Energy utilization system

Electric locomotive operation characteristic curve

The experimental results are shown in Figures _{dc}), the power of the super capacitor (_{sc}), and the voltage of the super capacitor (_{sc}). Figure _{L}), the working current (_{L}), and the feedback power of electric locomotive (_{M}). The no-load voltage of the DC bus is 1500V.

Results of field experiment: bus voltage

Results of field experiment: energy feedback subsystem power_{L}, energy feedback subsystem current_{L}, and electric locomotive feedback power

In the stage of starting, the starting power supplied by the traction substation to the electric locomotive flowed through the line impedance, causing a decrease in the DC bus voltage. To prevent the huge decrease in bus voltage, the energy storage subsystem released energy to the DC bus with a peak power of 3MW. The DC bus voltage was finally stabilized at about 1400V, and the super capacitor voltage was reduced from 1000V to 700V. In the stage of moving at a constant speed, the operating power of the electric locomotive was low, the DC bus voltage was approximately restored to 1500V, the energy storage subsystem entered the standby mode, and super capacitor voltage remained constant at 700V. When entering the braking stage, the regenerative feedback energy was charged to the DC bus, causing the bus voltage to rise beyond the preset value, and the energy storage subsystem was switched from standby mode to charging mode. At the same time, the energy feedback subsystem received the command to start its operation.

It can be seen from Figure

This paper proposes an optimized scheme for the reasonable energy distribution between energy storage subsystem and energy feedback subsystem. This scheme adopts an improved voltage-current dual closed-loop control strategy. The experimental results show that the maximum absorption power of the energy feedback subsystem is 0.3 times of the peak power of the electric locomotive braking, with a capacity utilization efficiency of 81% and that the energy absorbed by the energy storage subsystem is 0.371 times of the energy of electric locomotive braking. The fluctuation in the DC bus voltage of traction network and the recycling rate of the regenerative braking energy are within the normal range. It is verified by the simulation and experiment that the proposed scheme can effectively overcome the shortcomings of low energy density of energy storage subsystem and weak antishock power of energy feedback subsystem. The proposed scheme has improved the capacity utilization of the energy feedback devices and shows good economic benefits.

The data used to support the findings of this study are available from the corresponding author upon request.

The authors declare that they have no conflicts of interest.

This research is financially supported by the Science and Technology Research Project for Strategic Emerging Industry of Hunan Province (No. 2016GK4027) and the National Natural Science Foundation of China (No. 61573298).