Traction photovoltaic power generation system capable of recovering braking energy

Abstract

The invention relates to the technical field of photovoltaic power generation, and particularly discloses a traction photovoltaic power generation system for braking energy recovery, which comprises a photovoltaic power generation unit, a braking energy recovery unit, a multi-source collaborative management unit, a main power conversion unit and a system control unit. Wherein the multi-source collaborative management unit is dynamically optimized through a virtual impedance synthesizer of the multi-source collaborative management unit, different equivalent input impedances are given to two input ports, impedance matching is achieved, a hierarchical coordination control strategy is combined, braking power is actively stabilized, photovoltaic output is flexibly adjusted, and therefore the overall energy conversion efficiency, operation stability and dynamic performance of the system are improved.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic power generation technology, and specifically relates to a traction photovoltaic power generation system for brake energy recovery. Background Technology

[0002] In the fields of rail transit and new energy technology, energy recovery and efficient utilization of renewable energy are key research directions for improving overall system energy efficiency and achieving green and low-carbon operation. Among them, recovering and utilizing the energy generated by train braking and using photovoltaic power generation technology to provide auxiliary power have become important technological directions in this field.

[0003] The traction photovoltaic power generation system with regenerative braking energy aims to integrate two energy sources, supplying power to the traction system or auxiliary loads through a unified power electronic conversion device, thereby improving the overall energy utilization efficiency. The basic principle of this system is to process braking energy and photovoltaic power through a DC-DC converter, then feed them into the DC bus or directly supply the load.

[0004] In existing technologies, regenerative braking and photovoltaic (PV) power generation are typically connected in parallel to share the same DC-DC converter. However, regenerative braking energy exhibits significant instantaneous high-power pulse characteristics, with its power amplitude fluctuating drastically and randomly, while the output power of PV power generation is relatively stable and varies slowly depending on sunlight conditions. Directly connecting these two energy sources with such different characteristics to the same converter input will cause drastic fluctuations in the voltage and current waveforms at the input, resulting in a severe mismatch between the input impedance and the source-end output impedance of the DC-DC converter.

[0005] This mismatch not only causes frequent shifts in the converter's operating point, reducing maximum power point tracking efficiency, but also generates additional switching stress and circulating current losses within the converter, significantly weakening the system's overall energy conversion efficiency and operational stability. Therefore, effectively managing the diverse energy inputs from multiple sources with vastly different characteristics and resolving the resulting power matching and impedance mismatch challenges is a critical technical issue that urgently needs to be addressed to improve the performance of such hybrid power generation systems. Summary of the Invention

[0006] The purpose of this invention is to provide a traction photovoltaic power generation system for brake energy recovery, in order to solve the problems in the prior art where the large differences in characteristics between brake energy and photovoltaic power lead to input impedance mismatch, reduced conversion efficiency, and decreased system stability when connected in parallel to the same converter.

[0007] The technical solution of the present invention is a traction photovoltaic power generation system for braking energy recovery, which includes a photovoltaic power generation unit, a braking energy recovery unit, a multi-source collaborative management unit, a main power conversion unit, and a system control unit.

[0008] The photovoltaic power generation unit is used to convert solar energy into direct current (DC) power, and its output is connected to the first input of the multi-source collaborative management unit. The photovoltaic power generation unit includes a photovoltaic cell array connected in series and a first DC-DC pre-regulator. The first DC-DC pre-regulator employs a maximum power point tracking (MPPT) algorithm, and its control objective is to ensure that the output voltage and current of the photovoltaic cell array operate at a preset maximum power point to obtain maximum photovoltaic power generation.

[0009] The braking energy recovery unit is used to capture and convert the regenerative braking energy generated during train braking, and its output is connected to the second input of the multi-source cooperative management unit. This braking energy recovery unit includes a braking chopper, an energy storage medium, and a second DC-DC pre-regulator. The braking chopper is connected to the train traction DC bus and is used to guide the regenerative braking energy to the energy storage medium during braking. The energy storage medium is a supercapacitor module, used to absorb high-power pulses generated during braking. The second DC-DC pre-regulator is connected to the output of the supercapacitor module, and its control objective is to maintain the output voltage of the supercapacitor module within a preset stable range, while actively smoothing the output power.

[0010] The multi-source collaborative management unit is the core device for solving the impedance mismatch problem. Its inputs receive a first DC power supply from the photovoltaic power generation unit and a second DC power supply from the regenerative braking unit. This unit includes a dual-input coupling converter and a virtual impedance synthesizer. The dual-input coupling converter has two electrically isolated input ports and a common output port. Internally, it employs an interleaved parallel magnetic integration structure to synthesize the energy from the two input ports on the primary side of the transformer through magnetic coupling. The virtual impedance synthesizer is built into the control loop of the dual-input coupling converter. Its function is to dynamically calculate and assign different equivalent input impedances to the two input ports of the dual-input coupling converter based on the real-time acquired voltage and current values ​​of the first and second DC power supplies.

[0011] Furthermore, the impedance calculation and assignment process of the virtual impedance synthesizer is as follows: The system control unit acquires the output power values ​​of the photovoltaic power generation unit, the braking energy recovery unit, and the load demand power value of the main power conversion unit in real time. The virtual impedance synthesizer incorporates a multi-objective optimization algorithm. The optimization objectives of this algorithm include minimizing the voltage ripple at the input of the dual-input coupled converter, maximizing its overall transmission efficiency, and ensuring stable input power of the main power conversion unit. The algorithm uses the equivalent input impedance on the photovoltaic side and the equivalent input impedance on the braking side as optimization variables, and uses the output characteristic equations of the two input sources and the circuit state equation of the dual-input coupled converter as constraints to perform online iterative solutions. The optimal impedance value obtained by the solution is converted into the corresponding duty cycle adjustment command and injected into the pulse width modulation signal controlling the switching transistors at the two input ports of the dual-input coupled converter, thereby realizing dynamic reshaping of the port impedance at the circuit level.

[0012] The main power conversion unit converts the synthesized DC power output from the multi-source collaborative management unit into electrical energy that meets the requirements of the traction system or auxiliary load. The input of the main power conversion unit is connected to the output of the multi-source collaborative management unit. This unit is a bidirectional DC-AC inverter or DC-DC converter, and its specific topology is determined according to load requirements.

[0013] The system control unit serves as the central decision-making and coordination core of the entire system. It establishes bidirectional communication connections with the first DC-DC pre-regulator of the photovoltaic power generation unit, the second DC-DC pre-regulator of the braking energy recovery unit, the virtual impedance synthesizer of the multi-source collaborative management unit, and the main power conversion unit. The system control unit internally operates a hierarchical coordination control strategy.

[0014] In one embodiment of the present invention, the hierarchical coordinated control strategy includes an energy management strategy at the upper system level and a local control strategy at the lower device level. The system-level energy management strategy formulates a global power allocation plan based on a preset operating schedule, real-time load power prediction, and weather forecast information. The core of this plan is to dynamically set the output power suppression target value of the regenerative braking unit and the weighting coefficient for maximum power point tracking of the photovoltaic power generation unit. The local control strategy at the lower device level receives the set values ​​from the upper level. Specifically, the second DC-DC pre-regulator of the regenerative braking unit performs model predictive control with power suppression as the objective, the first DC-DC pre-regulator of the photovoltaic power generation unit performs weighted maximum power point tracking control, and the virtual impedance synthesizer of the multi-source collaborative management unit performs the aforementioned multi-objective impedance optimization algorithm.

[0015] Furthermore, the model predictive control process executed by the second DC-DC pre-regulator is as follows: A discrete-time system predictive model is established using the state of charge (SOC) of the supercapacitor module, its output voltage, and the power mitigation target value from the upper layer as state variables, and the duty cycle of the second DC-DC pre-regulator as the control variable. In each control cycle, the controller, based on the current state, continuously optimizes the control variable sequence for the next few cycles to minimize the deviation between the predicted output power trajectory and the mitigation target value, while maintaining the SOC of the supercapacitor module within a preset safety window. Finally, the first control variable in the optimized sequence is applied to the current cycle.

[0016] Furthermore, the weighted maximum power point tracking (MPPT) control process executed by the first DC-DC pre-regulator is as follows: Its MPPT algorithm's objective function does not simply pursue maximum instantaneous power, but introduces a dynamic weighting coefficient issued by the system control unit. This objective function is modified to maximize the product of photovoltaic output power and the weighting coefficient. When the system load demand is low or braking energy is sufficient, the weighting coefficient is lowered, and the first DC-DC pre-regulator will actively deviate from the theoretical maximum power point, slightly reducing photovoltaic output in exchange for a smoother power output characteristic, thereby better cooperating with the impedance matching work of the multi-source collaborative management unit.

[0017] In one embodiment of the present invention, the interleaved parallel magnetic integrated structure of the dual-input coupled converter is as follows: two input ports are each connected to an independent primary winding, and these two primary windings are interleaved and wound on different columns of the same high-frequency transformer core with a specific phase difference. A common output port is connected to a secondary winding, which is wound on the central column of the core. By designing the turns ratio and interleaved phase of the primary winding, the high-frequency current ripple from the two input terminals is partially canceled in the magnetic circuit, thereby significantly reducing the amplitude of the current ripple transmitted to the secondary and input terminals. This provides a smoother circuit basis for the virtual impedance synthesizer to achieve fine impedance control.

[0018] In one embodiment of the present invention, the system control unit is also connected to a complete status monitoring and protection module. This module collects voltage, current, and temperature parameters of key nodes within the system in real time and compares them with preset safety thresholds. When any parameter exceeds its limit, the system control unit immediately executes a preset protection sequence. The priority of the protection sequence, from high to low, is as follows: isolate the faulty branch, switch to standby control mode, and perform graded power reduction operation. Simultaneously, all operating data, fault events, and control commands are recorded in non-volatile memory for subsequent system performance analysis and maintenance.

[0019] Compared with the prior art, the advantages and positive effects of the present invention are as follows: 1. This invention creatively solves the mismatch problem when braking energy and photovoltaic power are input in parallel by introducing a multi-source collaborative management unit, especially its internal virtual impedance synthesizer and dual-input coupling converter, from the fundamental physical level of impedance matching.

[0020] 2. The virtual impedance synthesizer dynamically allocates the optimal equivalent input impedance to two power supplies with different characteristics through an online multi-objective optimization algorithm, so that the operating point of the DC-DC converter is always kept in the high efficiency range, significantly reducing the switching stress and circulating current loss caused by impedance mismatch, thereby greatly improving the overall energy conversion efficiency and power transmission capability of the system.

[0021] 3. This invention adopts a hierarchical and coordinated system-level control architecture, decoupling yet coordinating global energy management with local device control. The upper-level system control unit performs forward-looking planning based on operational information, while lower-level units execute advanced algorithms such as model predictive control and weighted maximum power point tracking. This architecture enables the system not only to passively adapt to energy source fluctuations but also to actively suppress dynamic power pulses and flexibly adjust photovoltaic output, reducing drastic changes in input power at the source. This creates more stable operating conditions for impedance matching of the multi-source collaborative management unit, greatly enhancing the system's operational stability and robustness under complex operating conditions.

[0022] 4. This invention employs a dual-input coupled converter with an interleaved parallel magnetic integrated structure in its hardware topology. This structure utilizes magnetic coupling and interleaved phase technology to partially cancel the ripple of the two input currents, effectively reducing the input and output current ripple. This reduces the need for filtering components and increases power density; furthermore, the cleaner current waveform further improves the accuracy and response speed of virtual impedance control, forming a positive cycle of mutual reinforcement between the hardware topology and the control algorithm. This results in superior dynamic performance and power quality when the system responds to instantaneous braking energy impacts. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall technical solution architecture of the traction photovoltaic power generation system for brake energy recovery proposed in this invention; Figure 2 This is a logical flow diagram of the hierarchical coordination control strategy in this invention; Figure 3 This is a schematic diagram of the energy flow and information flow of the photovoltaic power generation unit and the braking energy recovery unit in this invention through a multi-source collaborative management unit; Figure 4 This is a schematic diagram of the interleaved parallel magnetic integrated structure of the dual-input coupled converter in this invention. Detailed Implementation

[0024] This invention provides a traction photovoltaic power generation system for regenerating braking energy. Please refer to the appendix for the overall technical architecture. Figures 1 to 4 This system aims to efficiently integrate solar energy and regenerative braking energy from trains, which have vastly different characteristics. Through innovative hardware topology and collaborative control strategies, it fundamentally solves the impedance mismatch problem when the two are connected in parallel, thereby significantly improving the overall energy conversion efficiency, power transmission capacity, and operational stability of the system. The system consists of five core components: a photovoltaic power generation unit, a braking energy recovery unit, a multi-source collaborative management unit, a main power conversion unit, and a system control unit. These units are tightly coupled through a power bus and a high-speed communication network, forming an organic whole.

[0025] The core function of the photovoltaic power generation unit is to convert solar radiation energy into DC power that can be used by the traction system or auxiliary loads. The output of this unit is connected to the first input of the multi-source collaborative management unit via a DC bus. The photovoltaic power generation unit specifically consists of a photovoltaic cell array and a first DC-DC pre-regulator. The photovoltaic cell array is composed of multiple photovoltaic cell modules combined in series and parallel. Its electrical output characteristics exhibit strong nonlinearity, and the output voltage and current are affected by multiple factors such as solar irradiance, ambient temperature, and the degree of aging of the cells themselves.

[0026] The first DC-DC pre-regulator adopts a boost, buck, or buck-boost topology. Its input is directly connected to the output of the photovoltaic array, and its output is connected to the DC bus leading to the multi-source collaborative management unit. The core control objective of this first DC-DC pre-regulator is to execute a maximum power point tracking (MPPT) algorithm, ensuring that the operating point of the controlled photovoltaic array dynamically tracks and stabilizes near a preset maximum power point. The MPPT algorithm periodically perturbs the switching duty cycle of the first DC-DC pre-regulator, samples the output voltage and current of the photovoltaic array, calculates the instantaneous output power, and determines the direction of duty cycle adjustment for the next cycle by comparing the power change trends before and after the perturbation, ultimately causing the output power of the photovoltaic array to converge to its maximum value.

[0027] The first DC-DC pre-regulator contains high-precision voltage and current sensors to acquire the voltage and current signals at its input terminals in real time, with a sampling frequency of no less than 20 kHz. The acquired raw voltage and current data are passed through an anti-aliasing low-pass filter and then sent to an analog-to-digital converter to be converted into digital quantities. Subsequently, they are encapsulated into data frames of a specific format and periodically sent to the system control unit via an isolated serial peripheral interface or a controller area network bus.

[0028] The power switching devices of the first DC-DC pre-regulator are made of gallium nitride or silicon carbide to reduce switching losses and allow for higher operating frequencies, with the switching frequency set between 100 kHz and 500 kHz. A filter network combining electrolytic capacitors and film capacitors is configured on the output side to smooth voltage ripple caused by the switching frequency, ensuring the quality of the DC voltage output to the multi-source co-management unit.

[0029] The core function of the braking energy recovery unit is to capture, temporarily store, and mitigate the regenerative braking energy generated by the train during braking. The output of this unit is connected to the second input of the multi-source collaborative management unit via another independent DC bus. The braking energy recovery unit specifically comprises a braking chopper, an energy storage medium, and a second DC-DC pre-regulator. The braking chopper is a high-power bidirectional DC-DC converter; its high-voltage side is directly connected in parallel to the train traction DC bus, and its low-voltage side is connected to the energy storage medium.

[0030] When the train enters electric braking mode, the traction motor transforms into a generator, producing a regenerative voltage on the traction DC bus that is higher than the bus's rated voltage. Upon detecting this voltage rise, the brake chopper immediately activates, controlling the switching on and off of its internal insulated-gate bipolar transistors (IGBTs) or metal-oxide-semiconductor field-effect transistors (MOSFETs) to chop excess electrical energy on the traction DC bus in pulse form and guide it to the energy storage medium on the low-voltage side. The brake chopper employs peak current control mode, with its current loop reference value calculated and issued in real-time by the system control unit based on the fluctuation amplitude of the traction DC bus voltage. This ensures rapid absorption of braking energy to prevent overvoltage while avoiding unnecessary interference to the traction system. The energy storage medium is a supercapacitor module composed of multiple supercapacitor cells connected in series and parallel. Supercapacitor modules feature high power density, long cycle life, and rapid charging and discharging capabilities, making them ideal for absorbing high-power, short-duration pulses generated during braking.

[0031] The supercapacitor module is equipped with an active equalization management system. This system monitors the terminal voltage of each supercapacitor cell and transfers energy from cells with higher voltage to cells with lower voltage through switching resistors or inductor-capacitor resonance, ensuring the consistency of voltage across all cells within the module and thus maximizing the module's usable capacity and lifespan. A second DC-DC pre-regulator is connected between the supercapacitor module and the second input terminal of the multi-source collaborative management unit. Its topology is typically a bidirectional buck-boost converter. The main control objective of the second DC-DC pre-regulator is to maintain the supercapacitor module's output voltage within a preset stable range, such as from 50% to 95% of the rated voltage, while actively smoothing its output power. To achieve power smoothing, the second DC-DC pre-regulator integrates high-bandwidth voltage and current sensors to collect the supercapacitor module's terminal voltage, its own output current, and the supercapacitor module's current in real time. These data are sampled at frequencies above 10 kHz and processed in real time by a digital signal processor.

[0032] The control core of the second DC-DC pre-regulator executes a model predictive control algorithm. This algorithm first establishes a discrete-time system prediction model, whose state variables include the state of charge of the supercapacitor module, the output voltage of the supercapacitor module, and the output current of the second DC-DC pre-regulator. The control variable is the switching duty cycle of the second DC-DC pre-regulator. In each control cycle, for example, a cycle of 100 microseconds, the controller, based on the currently measured state variables, uses this prediction model to continuously extrapolate the trajectory of system state changes over the next 10 to 20 control cycles.

[0033] The controller's optimization objective is to find an optimal duty cycle sequence that minimizes the sum of squared cumulative deviations between the predicted output power trajectory and the power smoothing target value issued by the system control unit, while simultaneously constraining the supercapacitor module's state of charge within a safe window of 20% to 80%. The optimization process is performed online using a quadratic programming solver, and the first duty cycle value in the optimal control sequence output by the solver is immediately applied to the current control cycle. Through this rolling optimization and feedback correction mechanism, the second DC-DC pre-regulator can proactively smooth its output power, effectively suppressing the impact of braking energy pulses on the downstream system.

[0034] The multi-source collaborative management unit is the core innovative device of this invention. Its physical location is between the photovoltaic power generation unit, the braking energy recovery unit, and the main power conversion unit. Its electrical interface includes a first input terminal, a second input terminal, and a common output terminal. Its function is to solve the impedance mismatch problem when photovoltaic DC power and braking DC power are input in parallel. The multi-source collaborative management unit consists of two key parts: a dual-input coupling converter and a virtual impedance synthesizer. The dual-input coupling converter is a special type of isolated DC-DC converter with two electrically isolated input ports and a common output port. Internally, it adopts an interleaved parallel magnetic integration structure; for details, please refer to the appendix. Figure 4 This structure includes a high-frequency transformer core, typically of type EE or PQ. Two input ports are connected to two independent primary windings, denoted as the first primary winding and the second primary winding. The first and second primary windings are alternately wound on the two outer pillars of the core with a specific phase difference, such as 180 degrees. A common output port is connected to a secondary winding wound on the central pillar of the core. Each of the two primary windings drives a full-bridge or half-bridge power switching circuit.

[0035] By designing the turns ratio of the first and second primary windings and the staggered phase of the drive signals from the two sets of switching circuits, the high-frequency current ripple generated by the first DC current from the photovoltaic power generation unit and the second DC current from the regenerative braking unit produces opposite magnetic flux components in the transformer's magnetic circuit. These two magnetic flux components partially cancel each other out at the central column, thereby significantly reducing the amplitude of the current ripple transmitted to the secondary winding and reflected back to the primary input. This structure not only reduces the capacitance requirements of the input and output filter capacitors and increases power density, but more importantly, it provides a circuit environment with lower ripple content for subsequent virtual impedance control, which is beneficial for achieving more precise control.

[0036] The virtual impedance synthesizer is a software algorithm module built into the digital control loop of a dual-input coupled converter (DIC). It is not a physical resistor or inductor, but rather dynamically changes the equivalent input impedance characteristics of the two input ports of the DIC through a control algorithm. The input signals of the virtual impedance synthesizer include the real-time acquired voltage and current values ​​of the first DC current, the voltage and current values ​​of the second DC current, and the input signals of the third DC current. These signals are acquired through a high-precision isolated sampling circuit and sent to the digital processor of the virtual impedance synthesizer. The core of the virtual impedance synthesizer is a multi-objective optimization algorithm. The execution cycle of this algorithm is synchronized with the switching cycle of the DIC, typically ranging from 10 to 50 microseconds.

[0037] In each control cycle, the algorithm initiates and executes the following steps: First, the system control unit sends three key global parameters to the virtual impedance synthesizer via the communication bus: the real-time output power of the photovoltaic power generation unit, the real-time output power of the regenerative braking unit, and the real-time load demand power of the main power conversion unit. Next, the virtual impedance synthesizer defines two optimization variables: the equivalent input impedance on the photovoltaic side and the equivalent input impedance on the regenerative braking side. The algorithm's objective function comprises three sub-terms: the first sub-term is the sum of the effective values ​​of the voltage ripple at the two input ports of the dual-input coupled converter, with the objective of minimizing it; the second sub-term is the instantaneous conversion efficiency calculated based on the loss model of the dual-input coupled converter, with the objective of maximizing it; and the third sub-term is the fluctuation rate of the input power of the main power conversion unit, with the objective of minimizing it. These three sub-terms are combined into a total objective function using preset weighting coefficients.

[0038] The algorithm's constraints include the output characteristic equations of the two input sources, namely the voltage-current relationship at the maximum power point of the photovoltaic array under the current operating conditions, and the voltage-charge relationship of the supercapacitor module under the current state of charge; it also includes the circuit state equations of the dual-input coupled converter under a specific duty cycle, describing the relationship between input voltage, input current, output voltage, transformer turns ratio, and switching states. The virtual impedance synthesizer's built-in solver, such as a sequential quadratic programming solver or an interior-point solver, iteratively solves the overall objective function online under these constraints, seeking the optimal combination of the photovoltaic-side equivalent input impedance and the braking-side equivalent input impedance.

[0039] The solution process typically takes only a few microseconds. After obtaining the optimal impedance value, the virtual impedance synthesizer converts it into a corresponding duty cycle adjustment command based on the circuit parameters of the dual-input coupled converter. Specifically, for the photovoltaic input port, the duty cycle command is determined by the photovoltaic equivalent input impedance, the voltage value of the first DC current, and the output voltage of the dual-input coupled converter; for the braking input port, the duty cycle command is determined by the braking equivalent input impedance, the voltage value of the second DC current, and the output voltage of the dual-input coupled converter. These two duty cycle adjustment commands are injected into the pulse width modulation signal generators that control the first and second primary-side switches of the dual-input coupled converter, thereby adjusting the on-time of the two input switches in real time. Through this mechanism, the input impedance seen from the photovoltaic power generation unit and the braking energy recovery unit is dynamically reshaped into the optimal value calculated by the algorithm, enabling the dual-input coupled converter to automatically adapt to the output characteristics of two power sources with different characteristics, forcing them to operate in a high-efficiency impedance matching region, fundamentally eliminating circulating current losses and switching stress caused by impedance mismatch.

[0040] The main power conversion unit converts the stable DC power output from the multi-source collaborative management unit, which has undergone impedance matching and synthesis, into the electrical energy required by the final load. The input of the main power conversion unit is directly connected to the output of the multi-source collaborative management unit. The specific topology of the main power conversion unit varies depending on the application scenario. If the load is a traction motor drive system, the main power conversion unit is typically a three-phase two-level or three-level bidirectional DC-AC inverter. This inverter uses space vector pulse width modulation technology to convert the input DC power into three-phase AC power with adjustable amplitude and frequency to drive asynchronous or permanent magnet synchronous traction motors.

[0041] The DC-side support capacitor of the inverter needs to withstand power fluctuations from the multi-source collaborative management unit, and its capacitance value is calculated and determined based on the system's rated power and the allowable DC voltage fluctuation range. If the load is a train auxiliary power system, such as lighting, air conditioning, or battery charging, the main power conversion unit may be an isolated DC-DC converter, converting the DC voltage to the voltage level required by the auxiliary system, such as 110V DC or 380V AC. The main power conversion unit also integrates comprehensive protection functions, including overvoltage protection, undervoltage protection, overcurrent protection, overheat protection, and short-circuit protection. Its control commands are received from the system control unit, and closed-loop control is performed based on the power or voltage commands issued by the system control unit.

[0042] The system control unit is the central decision-making, coordination, and monitoring core of the entire system. Its hardware platform is typically built on a multi-core microprocessor or field-programmable gate array (FPGA), possessing powerful real-time computing and multi-tasking capabilities. The system control unit establishes bidirectional communication connections with the first DC-DC pre-regulator of the photovoltaic power generation unit, the second DC-DC pre-regulator of the regenerative braking unit, the virtual impedance synthesizer of the multi-source collaborative management unit, and the main power conversion unit via a high-speed isolated communication network. The communication protocol employs a real-time Ethernet protocol with deterministic latency or a time-triggered protocol to ensure the real-time performance and reliability of control commands and status information transmission. The system control unit internally runs a hierarchical coordinated control strategy; the logical flow framework of this strategy is described in the appendix. Figure 2 .

[0043] The hierarchical coordinated control strategy is clearly divided into two levels: an upper-level system-level energy management strategy and a lower-level device-level local control strategy. The upper-level system-level energy management strategy plays the role of a global planner. Its decision-making is based on three parts of information: First, there is a pre-set train operating timetable, from which the traction, cruising, and braking conditions of trains in specific sections and their time distribution can be predicted; Second, a real-time load power prediction model is established based on historical data and real-time vehicle speed and slope information. Third, it receives weather forecasts for the next few hours via wireless networks, especially predictions of solar irradiance and cloud cover.

[0044] The core algorithm of the energy management strategy, based on this information, dynamically formulates a global power allocation plan with the goal of maximizing overall system operating efficiency and minimizing impact on the traction power grid. This plan outputs two key setpoints: first, a power smoothing target value sent to the regenerative braking unit, which is a time-varying power reference curve designed to guide the second DC-DC pre-regulator in planning the charging and discharging power of the supercapacitor module in advance, ensuring its output power is as smooth as possible; second, a maximum power point tracking weighting coefficient sent to the photovoltaic power generation unit, which is a dynamic variable between 0 and 1. The local control strategy at the lower-level device level then plays the role of an efficient executor.

[0045] After receiving the setpoints from the system control unit, each unit independently runs its own advanced control algorithm. The second DC-DC pre-regulator of the regenerative braking unit performs model predictive control as described above, and the power reference trajectory in its objective function is the power smoothing target value issued by the upper layer. The first DC-DC pre-regulator of the photovoltaic power generation unit performs weighted maximum power point tracking control. Its objective function is modified to maximize the product of photovoltaic output power and weighting coefficients. Mathematically, its core decision-making logic is as follows: In each control cycle, the algorithm finds an operating voltage at which the product of photovoltaic output power and the dynamic weighting coefficients issued by the system control unit is maximized. When the system load demand is low, or when a large amount of regenerative braking energy is predicted to be injected according to the operating schedule, the upper-level energy management strategy will lower the weighting coefficients, for example, from 1.0 to 0.7. At this time, the first DC-DC pre-regulator will actively deviate from the theoretical instantaneous maximum power point and operate at an operating point with slightly lower output power but a smoother power change rate. This flexible adjustment, at the cost of slightly sacrificing a small amount of photovoltaic power generation, achieves active smoothing of photovoltaic output characteristics, greatly reducing the power fluctuation amplitude that the multi-source collaborative management unit needs to deal with when performing impedance matching.

[0046] The virtual impedance synthesizer of the multi-source collaborative management unit executes the aforementioned multi-objective impedance optimization algorithm, and the global power parameters it receives are real-time data from the system control unit. Through this hierarchical, decoupled, and collaborative architecture, the system achieves closed-loop control from global optimization to precise local execution.

[0047] The system control unit also integrates a complete status monitoring and protection module. This module collects over 50 analog and digital signals in real time through a sensor network distributed across key nodes of the system, including but not limited to DC bus voltages, branch currents, main power device heatsink temperatures, ambient temperature, supercapacitor module individual voltages, and transformer winding temperatures. All analog signals are processed by a high-resolution synchronous sampling analog-to-digital converter after signal conditioning circuitry, and the sampled data is sent to the processor via direct memory access. The protection module has preset multi-level safety thresholds, including warning thresholds and trip thresholds. The system control unit scans all monitored parameters at 1-millisecond intervals and compares them with the thresholds. Once any parameter exceeds the trip threshold, such as a branch current exceeding 200% of its rated value, the system control unit immediately interrupts the current control task and executes the preset multi-level protection sequence.

[0048] The protection sequence is executed sequentially from highest to lowest priority: the highest priority is fault isolation, which physically disconnects the faulty branch from the main system circuit by controlling the corresponding solid-state relays or contactors; if the fault is recoverable or a minor over-limit, the system switches to a backup control mode, such as switching the virtual impedance synthesizer to a fixed impedance mode or switching model predictive control to proportional-integral control; the final level is graded power reduction operation, which gradually reduces the total output power of the system according to a preset power reduction curve until the parameters return to normal or the system safely shuts down. All status data, control command logs, fault event records, and protection action sequences during operation are written in real time to the non-volatile memory on the system control unit board, with a storage capacity sufficient to record 30 consecutive days of operating data. This data can be exported via Ethernet interface or wireless communication module for subsequent in-depth system performance analysis, energy efficiency assessment, fault diagnosis, and preventive maintenance planning.

[0049] Please refer to the appendix for the process of energy flow and information flow working together in the entire system. Figure 3 Under typical daytime operating conditions, with ample solar irradiance, the photovoltaic power generation unit outputs maximum power, while the train operates according to its timetable, generating periodic braking energy. Photovoltaic power serves as the first DC power source, and regenerative braking energy serves as the second DC power source, both input to the multi-source collaborative management unit.

[0050] Based on the timetable and meteorological information, the system control unit calculates that the photovoltaic output needs to be moderately suppressed during the current period to reserve space for the upcoming braking energy. Therefore, it issues a lower weighting coefficient to the photovoltaic power generation unit and a smooth power stabilization target curve to the braking energy recovery unit. The first DC-DC pre-regulator of the photovoltaic power generation unit adjusts its operating point according to the weighting coefficient, resulting in a slightly reduced but more stable power output. The second DC-DC pre-regulator of the braking energy recovery unit adjusts the charging and discharging strategy of the supercapacitor module in advance according to the stabilization target.

[0051] The virtual impedance synthesizer of the multi-source collaborative management unit acquires real-time power, voltage, and current information from the two power sources, as well as the load requirements of the main power conversion unit. It then rapidly calculates the optimal equivalent input impedance using a multi-objective optimization algorithm and converts this into duty cycle commands to control the dual-input coupled converter. The dual-input coupled converter utilizes its interleaved parallel magnetic integration structure to efficiently and with low ripple combine the two input power sources into a single output to the main power conversion unit.

[0052] The main power conversion unit converts the synthesized DC power into the required form of electrical energy to supply the load. Under the hierarchical coordination of the system control unit, the entire process achieves integrated operation of photovoltaic and braking energy with impedance matching at the physical level, smooth complementarity at the power level, and stable and efficient operation at the system level.

Claims

1. A braking energy recovery traction photovoltaic power system, characterized in that, The application relates to a photovoltaic power generation unit for converting solar energy into direct-current power, an output end of the photovoltaic power generation unit being connected to a first input end of a multi-source cooperative management unit, the photovoltaic power generation unit comprising a photovoltaic cell array and a first DC-DC pre-regulator connected in series, the first DC-DC pre-regulator adopting a maximum power point tracking algorithm; a braking energy recovery unit for capturing and converting regenerative braking energy generated during train braking, an output end of the braking energy recovery unit being connected to a second input end of the multi-source cooperative management unit, the braking energy recovery unit comprising a braking chopper, an energy storage medium and a second DC-DC pre-regulator, the braking chopper being connected to a train traction direct-current bus, the energy storage medium being a super capacitor module, and the second DC-DC pre-regulator being connected to an output end of the super capacitor module; the multi-source cooperative management unit, input ends of the multi-source cooperative management unit receiving first direct-current power from the photovoltaic power generation unit and second direct-current power from the braking energy recovery unit, the multi-source cooperative management unit comprising a double-input coupled converter and a virtual impedance synthesizer, the double-input coupled converter having two electrically isolated input ports and a common output port, and the double-input coupled converter internally adopting a magnetic integrated structure in interlaced parallel connection, the virtual impedance synthesizer being built-in in a control loop of the double-input coupled converter, and the virtual impedance synthesizer being used for dynamically calculating and giving different equivalent input impedances to the two input ports of the double-input coupled converter according to real-time collected voltage and current values of the first direct-current power and the second direct-current power; a main power conversion unit for converting synthesized direct-current power output by the multi-source cooperative management unit into an electric energy form meeting requirements of a traction system or auxiliary loads, an input end of the main power conversion unit being connected to an output end of the multi-source cooperative management unit; and a system control unit, the system control unit being bidirectionally connected with the first DC-DC pre-regulator of the photovoltaic power generation unit, the second DC-DC pre-regulator of the braking energy recovery unit, the virtual impedance synthesizer of the multi-source cooperative management unit and the main power conversion unit, and the system control unit internally running a hierarchical coordination control strategy. The impedance calculation and giving process of the virtual impedance synthesizer is as follows: the system control unit acquires output power values of the photovoltaic power generation unit, output power values of the braking energy recovery unit and load demand power values of the main power conversion unit in real time; the virtual impedance synthesizer is built-in with a multi-objective optimization algorithm, and optimization targets of the algorithm include minimizing voltage ripple of the input end of the double-input coupled converter, maximizing overall transmission efficiency of the double-input coupled converter and ensuring input power stability of the main power conversion unit; the algorithm takes equivalent input impedances of the photovoltaic side and the braking side as optimization variables, and takes output characteristic equations of the two input sources and circuit state equations of the double-input coupled converter as constraint conditions to perform online iterative solution; and optimal impedance values obtained through the solution are converted into corresponding duty ratio regulation instructions and are respectively injected into pulse width modulation signals for controlling switch tubes of the two input ports of the double-input coupled converter. The hierarchical coordination control strategy comprises an energy management strategy at an upper system level and a local control strategy at a lower device level. ​ ​ ​ 2. The braking energy recovery traction photovoltaic power system according to claim 1, wherein, ​ ​ ​ ​ 3. The braking energy recovery traction photovoltaic power system according to claim 1, wherein, ​ The system-level energy management strategy formulates a global power distribution plan based on preset operation schedule, real-time load power prediction and weather forecast information, and dynamically sets an output power damping target value of the brake energy recovery unit and a weight coefficient of the maximum power point tracking of the photovoltaic power generation unit; The lower-level device-level local control strategy receives the set value from the upper level, the second DC-DC pre-regulator of the brake energy recovery unit performs model predictive control targeting power damping, the first DC-DC pre-regulator of the photovoltaic power generation unit performs weighted maximum power point tracking control, and the virtual impedance synthesizer of the multi-source collaborative management unit performs a multi-objective impedance optimization algorithm.

4. The braking energy recovery traction photovoltaic power system according to claim 3, wherein, The model predictive control process performed by the second DC-DC pre-regulator is as follows: A discrete-time system prediction model is established with the state of charge, output voltage of the supercapacitor module and the power damping target value issued by the upper level as state variables, and the duty cycle of the second DC-DC pre-regulator as the control variable; In each control period, the controller optimizes the control variable sequence in the future several periods based on the current state, so that the deviation between the predicted output power trajectory and the damping target value is minimized, and the state of charge of the supercapacitor module is maintained within the preset safety window; The first control variable in the optimized sequence is finally applied to the current period.

5. The braking energy recovery traction photovoltaic power system according to claim 3, wherein, The weighted maximum power point tracking control process performed by the first DC-DC pre-regulator is as follows: The objective function of the maximum power point tracking algorithm is modified to maximize the product of the photovoltaic output power and the dynamic weight coefficient issued by the system control unit; When the system load demand is low or the brake energy is sufficient, the weight coefficient is adjusted to be low, and the first DC-DC pre-regulator actively deviates from the theoretical maximum power point.

6. The brake energy recovery traction photovoltaic power system according to claim 1, wherein, The interleaved parallel magnetic integration structure of the double-input coupled converter is as follows: Two input ports are connected to an independent primary winding, and the two primary windings are interleaved with a certain phase difference on different columns of the same high-frequency transformer magnetic core; The common output port is connected to a secondary winding, which is wound on the central column of the magnetic core; By designing the turn ratio and interleaving phase of the primary winding, the high-frequency current ripples from the two inputs are partially canceled in the magnetic circuit.

7. The brake energy recovery traction photovoltaic power system according to claim 1, wherein, The system control unit is also connected to a state monitoring and protection module; the state monitoring and protection module collects the voltage, current and temperature parameters of the key nodes in the system in real time, and compares them with the preset safety threshold; when any parameter is detected to be out of limit, the system control unit immediately executes the preset protection sequence.

8. The brake energy recovery traction photovoltaic power system according to claim 7, wherein, The priority of the protection sequence from high to low is: isolating the fault branch, switching to the backup control mode, and executing the graded power reduction operation.

9. The brake energy recovery traction photovoltaic power system according to claim 7, wherein, All operation data, fault events and control instructions are recorded in the non-volatile memory.

10. The brake energy recovery traction photovoltaic power system of claim 1, wherein, The main power conversion unit is a bidirectional DC-AC inverter or a DC-DC converter.

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