602results about "Propulsion by capacitors" patented technology

An energy management system can comprise a housing configured to receive energy storage assemblies within an interior region of the housing via one or more openings on a surface of the housing. One or more guide tracks positioned within the interior region can mechanically and electrically couple to the energy storage assemblies. One or more switches can electrically couple the energy storage assemblies in series to increase a voltage provided from energy storage assemblies to an electrical load and can electrically couple the energy storage assemblies in parallel to facilitate charging the energy storage assemblies from an energy source.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes a plurality of energy storage units that include a supercapacitor and an electrochemical battery. The system includes an energy controller that tracks historical power draw from the plurality of energy storage units over time in power tracking data, and that identifies a power draw based on the power tracking data. The energy controller switches between a first configuration and a second configuration based on the identified power draw. The first configuration is configured for drawing power from the electrochemical battery and disconnecting from the supercapacitor, while wherein the second configuration is configured for drawing power from the supercapacitor and disconnecting from the electrochemical battery.

The invention discloses a driving control method of a DAB converter and related equipment, and relates to the technical field of power electronic converter control, and the method comprises the steps: calculating a voltage transformation ratio based on an input voltage and an output voltage through a current stress adjustment module, and calculating an output power based on the output voltage and an output current, substituting the voltage transformation ratio and the output power into a current stress adaptive minimization algorithm to solve an internal phase shift angle; meanwhile, through a PI controller, an external shift phase angle is adjusted based on a difference value between the instruction voltage and the output voltage; outputting the inner phase shift angle and the outer phase shift angle to a PWM modulation generator to generate a switching tube driving signal; the DAB converter is controlled by the driving signal to realize rated voltage output and current stress minimization, so that the efficiency and reliability of the converter are improved.

An electric vehicle charging station for charging electric vehicles includes a plurality of energy storage reservoirs configured to receive and store energy from one or more power sources and / or one or more power generators; one or more power heads for charging the electric vehicles at the electric vehicle charging station, the multiple power heads receiving electrical power from the plurality of energy storage reservoirs, the multiple power heads each being configured for releasably connecting to each of the electric vehicles for charging at the electric vehicle charging station; and a computer control system configured to monitor a charging demand at each of the one or more power heads and to connect one or more of the plurality of energy storage reservoirs to one or more of the power heads based on the charging demand of the one or more power heads.

An electric vehicle (EV) charging station for fast charging (e.g. 5 to 15 minutes) an electric vehicle (EV). The EV charging station can be configured to include one or more energy storage device comprising multiple electric reservoir modules.

A system for powering an electric vehicle includes at least one electrochemical battery, at least one supercapacitor battery, a first relay disposed on a first electrical path between the at least one electrochemical battery and the electric vehicle, the first relay to connect or disconnect the at least one electrochemical battery to or from the electric vehicle, and a second relay disposed on a second electrical path between the at least one supercapacitor battery and the electric vehicle, the second relay to connect or disconnect the at least one supercapacitor battery to or from the electric vehicle. The system also includes a processor communicatively coupled to first and second relays, wherein the processor, responsive to a first condition, disconnects the at least one electrochemical battery from the electric vehicle via the first relay and connects the at least one supercapacitor battery to the electric vehicle via the second relay.

The invention discloses a fuel cell hybrid electric heavy truck power source optimization design method and system, and the method comprises the steps: building a target function of the total cost per unit travelled distance in a life cycle based on the basic parameters of a fuel cell, a power cell and a super capacitor, and the degradation parameters and hydrogen consumption of the fuel cell and the power cell; an energy management strategy of the fuel cell hybrid electric heavy truck is established based on the average required power of the truck and the SOC of the power cell and the super capacitor; and a cancer cell competition and transfer algorithm is adopted, under an energy management strategy, a minimum objective function meeting the driving working condition is searched, and energy size optimization is completed. According to the method, the power source of the fuel cell hybrid electric heavy truck is subjected to global optimization design by adopting the cancer cell competition and transfer algorithm, the service life of the power source is prolonged while the power performance of the truck is guaranteed, the manufacturing cost, degradation cost and hydrogen consumption of a hybrid power system are remarkably reduced, and the energy efficiency of the system is improved.

In a method for operating an electric vehicle, including a first energy storage device (e.g., a rechargeable battery storage device), a second energy storage device (e.g., a double-layer capacitor device), an energy supply unit which provides energy, for charging the first and / or second energy storage device, and a first electrical consumer connected to the second energy storage device via an intermediate circuit, the first energy storage device is connected to the energy supply unit via a bidirectional converter unit, the second energy storage device is connected to the energy supply unit, a first power flows from the first energy storage device to the second energy storage device if an intermediate circuit voltage falls below a definable voltage, and a second power flow from the second to the first energy storage device is prevented.

A system for powering an electric vehicle includes at least one electrochemical battery, at least one supercapacitor battery, a first relay disposed on a first electrical path between the at least one electrochemical battery and the electric vehicle, the first relay to connect or disconnect the at least one electrochemical battery to or from the electric vehicle, and a second relay disposed on a second electrical path between the at least one supercapacitor battery and the electric vehicle, the second relay to connect or disconnect the at least one supercapacitor battery to or from the electric vehicle. The system also includes a processor communicatively coupled to first and second relays, wherein the processor, responsive to a first condition, disconnects the at least one electrochemical battery from the electric vehicle via the first relay and connects the at least one supercapacitor battery to the electric vehicle via the second relay.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes a solar cell that generates energy in response to receiving light. The system includes an energy controller, which includes a processor and memory, that predicts an optimal time period for charging an energy storage unit based on information tracking discharging of the energy storage unit over time. The system includes trickle charging circuitry that provides the energy to the energy storage unit during the optimal time period, and the energy storage unit that stores the energy and discharges the energy to power at least one component, such as a vehicle propulsion mechanism.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes a plurality of energy storage units that include a supercapacitor and an electrochemical battery. The system includes plurality of energy storage units including a supercapacitor and an electrochemical battery, the supercapacitor comprising a plurality of selectable power sources, and an adder module including a processor. The processor is configured to execute instructions to selectively connect the supercapacitor or the electrochemical battery to an electric drivetrain to propel the vehicle. The processor may be configured to measure the selectable power sources and determine a set of the selectable power sources to connect to the system.

The invention relates to a hybrid energy storage control method for an urban rail transit energy router. The method comprises the following steps: S1, carrying out topological structure design and system compatibility configuration on the energy router; s2, impedance modeling and frequency division power distribution of the hybrid energy storage system are carried out; s3, fuzzy controller design and super capacitor SOC dynamic management are carried out; s4, carrying out membership function optimization and fuzzy control parameter setting; s5, multi-mode cooperative control and system operation optimization are carried out; according to the structure of the energy router and the power utilization characteristics of the rail transit system, working modes are divided, the working state of the system is optimized, and the system is kept in a reasonable working state. The method can effectively improve the utilization rate of energy and prolong the service life of the system.

The invention provides a new energy automobile energy closed-loop system, method and product based on waste heat cascade recovery. The system comprises a waste heat cascade recovery subsystem for collecting multi-source waste heat of the new energy automobile and converting the multi-source waste heat into electric energy; the dynamic energy management subsystem is used for storing electric energy and determining a power-on path of the new energy automobile according to the state of the new energy automobile, and the state of the new energy automobile comprises the speed change rate of the new energy automobile, the charge state of the super capacitor bank and the charge state of the lithium battery pack; and the self-powered closed-loop control subsystem is used for monitoring the temperature of the battery module in the power-on process of the new energy automobile and calling electric energy to drive a heater when the temperature of the battery module is lower than a preset temperature threshold value so as to realize closed-loop temperature control. Therefore, the waste heat utilization rate of the new energy vehicle can be improved and the closed-loop management of the energy of the whole vehicle can be optimized by performing stepped recovery on the waste heat of the new energy vehicle and supplying power to the vehicle based on thermoelectric conversion.

Systems and methods for monitoring and managing temperature of power packs of supercapacitors are disclosed. The system comprises a plurality of supercapacitor power packs associated with an electric motor. Further, an energy database is provided and configured to store data related to the charge of the supercapacitor power packs and thermal energy requirements related to the supercapacitor power packs.

An apparatus for adjusting a vehicle body height of a vehicle and generating power includes a rack gear connected to a wheel and configured to be moved in a vertical direction by a vertical movement of the wheel relative to a road surface, a pinion gear configured to be rotated by movement of the rack gear while engaging with the rack gear, a one-way bearing connected to the pinion gear and configured to be rotated together with the pinion gear, the one-way bearing being configured to operate to transmit a load when rotating in one direction and not to transmit a load when rotating in the other direction, an electric generator connected to the one-way bearing and configured to generate electricity by the rotation of the one-way bearing in one direction, and a capacitor connected to the electric generator and configured to accumulate electricity generated by the electric generator.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes a plurality of energy storage units that include a supercapacitor and an electrochemical battery. The system includes plurality of energy storage units including a supercapacitor and an electrochemical battery, the supercapacitor comprising a plurality of selectable power sources, and an adder module including a processor. The processor is configured to execute instructions to selectively connect the supercapacitor or the electrochemical battery to an electric drivetrain to propel the vehicle. The processor may be configured to measure the selectable power sources and determine a set of the selectable power sources to connect to the system.

An electrical energy recovery, storage, and distribution system that may be used in a vehicle. The system may include a supercapacitor configured to quickly store large amounts of energy. The system may also include multiple circuits operating at different voltage levels, such that an output voltage from the supercapacitor is useful over a larger voltage range and the system is more energy efficient.

A glass fiber-based structural composite offers an alternative or supplement to carbon fibers in areas such as battery storage. Through electroless deposition of conductive materials like copper and nickel, the glass fiber surface is made conducting and functions as a good current collector. By using anode and cathode materials like manganese (II, III) oxide and Zinc, cathode and anode mats on the copper- and nickel-coated glass fibers are created via hydrothermal and electro-deposition methods. In one example application, the anode and cathode mats are in an alternate square patterned arrangement using copper and nickel-coated glass fiber as a current collector. The device, with a capacity of >300 mAh / g at 0.1 A / g is assembled using an alternate system of epoxy and electrolyte. Uncoated pristine glass fiber ladened and patterned with electrolyte are used as a separator. Uncoated pristine glass fiber ladened with epoxy can be used as an insulator between two devices.

The hierarchical optimization control method in the vehicle following scene of the fuel cell hybrid electric vehicle comprises the following steps: acquiring vehicle driving data in real time, and inputting the vehicle driving data into a pre-trained working condition recognition model for recognition to obtain a real-time traffic working condition; inputting the real-time traffic condition into a pre-constructed model prediction vehicle-following controller for prediction, and performing optimization guidance on the prediction process of the model prediction vehicle-following controller based on a particle swarm algorithm to obtain an optimal vehicle control parameter; demand power of the fuel cell hybrid electric vehicle is obtained based on the optimal vehicle control parameters, and weighting Soc is calculated according to the demand power; inputting the required power and the weighted Soc as input variables into a fuzzy logic system for fuzzy processing to obtain an adjustment frequency; and inputting the required power and the adjusting frequency into a self-adaptive low-pass filter for frequency division processing. According to the method, the required power of the fuel cell hybrid electric vehicle can be reasonably distributed in the vehicle following scene.

A system includes a plurality of power modules connected in parallel and a variable current load controller coupled to the plurality of power modules. The input terminals of the plurality of power modules are configured to be coupled to an output of a fuel cell stack, and the output terminals of the plurality of power modules are configured to supply power to a forklift. The plurality of power modules is further configured to provide electrical isolation between the fuel cell stack and the forklift. The variable current load controller is configured to regulate power distribution among the plurality of power modules.

A hybrid battery for supplying electric power to a vehicle includes a terminal, one or more lithium-ion cells, one or more ultracapacitor cells, a DC / DC converter, and a controller. The one or more lithium-ion cells are connected to supply a first current to the terminal. The DC / DC converter is coupled in-series between the terminal and the one or more ultracapacitor cells. The one or more ultracapacitor cells and the DC / DC converter are connected to supply a second current to the terminal. The lithium-ion cells are connected in parallel with the one or more ultracapacitor cells and the DC / DC converter. The controller is in communication with the DC / DC converter to selectively modify the second current provided to the terminal.

Aspects of the present disclosure are directed to systems, devices, methods, and computer-readable storage medium for adaptive / dynamic thermal management of an electrical power system having variable electric loads, and components thereof. Thermal management may be driven at least partially by predicted / modeled thermal performance of the component to be managed, which may be calculated or modified using direct or indirect measurements. Embodiments may include adaptive thermal management of at least one of an energy storage system and an electric energy supply. Applications of this disclosure may include adaptive thermal management method for electric vehicles and non-mobility applications, particularly having variable electrical loads, which may impact performance or life of the application.

An apparatus comprises a power electronic energy conversion system comprising a first energy storage device configured to store DC energy and a first voltage converter configured to convert a second voltage from a remote power supply into a first charging voltage configured to charge the first energy storage device. The apparatus also includes a first controller configured to control the first voltage converter to convert the second voltage into the first charging voltage and to provide the first charging voltage to the first energy storage device during a charging mode of operation and communicate with a second controller located remotely from the power electronic energy conversion system to cause a second charging voltage to be provided to the first energy storage device during the charging mode of operation to rapidly charge the first energy storage device.

A vehicle system includes a first battery pack connected to a second battery pack via a flying capacitor multi-level inverter. The fling capacitor inverter has multiple inverter legs, with each inverter leg being arranged in a flying capacitor topology. A three phase motor is connected to the inverter. A controller connected to the motor and the inverter. The controller includes a memory storing instructions configured to cause the controller to control the inverter as a direct current (DC)-DC converter such that a circulating current passes through the motor, the first battery pack and the second battery pack.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes power packs and a photovoltaic array with interconnected photovoltaic cells that supplies electric charge to the power packs for charging the power packs. A charge management database stores data tracking respective charge cycles of the power packs based on the charging and discharging of the power packs. An energy control system controls flow of power in the system to control the charging and the discharging of the power packs, optimizes the flow of power in the system based on the respective charge cycles as tracked in the data stored in the charge management database, and updates the charge management database based on the optimization(s). An output interface outputs a status of the power packs based on the flow of power, for instance to indicate effect(s) of the optimization(s) on the power packs.

The invention provides a control method, device and system of a molten iron transportation system and electronic equipment, and relates to the technical field of molten iron car control. The method comprises the following steps: acquiring a motion distance and a motion constraint condition between a starting position and a target position of the molten iron transport vehicle; wherein the motion constraint conditions comprise the maximum speed, the sliding speed and the shortest sliding distance; the shortest sliding distance is smaller than the movement distance; determining a first acceleration control strategy according to the maximum speed and a preset S-shaped speed curve, and determining a second acceleration control strategy according to the maximum speed, the sliding speed, the shortest sliding distance and the preset S-shaped speed curve; wherein the preset S-shaped speed curve is constructed according to a sinx * sinx function; and determining a target control strategy according to the movement distance, the first acceleration control strategy and the second acceleration control strategy, and generating a power drive control instruction of the molten iron transport vehicle according to the target control strategy. The stability of the molten iron transport vehicle can be improved, and molten iron splashing is avoided.

The invention relates to the technical field of hybrid electric vehicle energy management, in particular to a hybrid electric vehicle layered reinforcement learning energy management method considering energy source life and energy consumption optimization. The method comprises the following steps: establishing an energy management system model and an energy source degradation model; energy source physical characteristics are analyzed, demanded power is processed in a layered mode, and an energy management learning strategy based on historical data is constructed; and energy management is implemented by combining the demand power change, the lithium battery, the super capacitor SOC and the degeneration degree of the energy source. Fuzzy filtering is adopted to shunt required power, a high-frequency peak value is borne by a super capacitor, and low-and-medium-frequency power is proportionally distributed by a lithium battery and a fuel battery according to the degradation degree; energy source degradation and deep reinforcement learning are fused, related parameter weighting is introduced into the ECMS, and lithium battery charging and discharging current is restrained. According to the method, comprehensive energy consumption can be reduced, energy source degradation is slowed down, the working condition application range is widened, overcharge and overdischarge of the lithium battery are avoided, the service life of the lithium battery is prolonged, and the SOC of the energy storage element is stabilized in a reasonable interval.

Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

The invention relates to the technical field of rail transit, in particular to a linear motor traction converter system which comprises a linear motor carrying truck, a traction carrying truck, an energy supplementing carrying truck and a quick plug connector. Wherein the linear motor carrying truck carries a linear motor and a section switch which are connected with each other; the traction carrying truck carries a traction converter and a super capacitor which are connected with each other; the energy supplementing carrying truck carries the battery charging unit; the quick-plug connectors comprise a first quick-plug connector and a second quick-plug connector; wherein the section switch is connected with the traction converter through the first quick plug connector. According to the scheme, through function decoupling and vehicle-mounted design, an original integrated system is decomposed into three core modules with independent maneuvering capacity, on-site hour-level rapid electrical assembly is achieved, and the core pain point of long deployment period is solved.