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In recent years, increasing attention has been given to reducing energy consumption in hydraulic excavators, resulting in extensive research in this field. One promising solution has been the integration of hydrostatic transmission (HST) and hydraulic pump/motor (HPM) configurations in parallel systems. However, these systems face challenges such as noise, throttling losses, and leakage, which can negatively impact both tracking accuracy and energy efficiency. To address these issues, this paper introduces an intelligent real-time prediction framework for system positioning, incorporating particle swarm optimization (PSO), long short-term memory (LSTM), a gated recurrent unit (GRU), and proportional–integral–derivative (PID) control. The process begins by analyzing real-time system data using Pearson correlation to identify hyperparameters with medium to strong correlations to the positioning parameters. These selected hyperparameters are then used as inputs for forecasting models. Independent LSTM and GRU models are subsequently developed to predict the system's position, with PSO optimizing four key hyperparameters of these models. In the final stage, the PSO-optimized LSTM-GRU models are employed to perform real-time intelligent predictions of motion trajectories within the system. Simulation and experimental results show that the model achieves a prediction deviation of less than 3 mm, ensuring precise real-time predictions and providing reliable data for system operators. Compared to traditional PID and LSTM-GRU-PID controllers, the proposed controller demonstrated superior tracking accuracy while also reducing energy consumption, achieving energy savings of up to 10.89% and 2.82% in experimental tests, respectively. [ABSTRACT FROM AUTHOR]

Configuring green power transmissions for heavy-industry marines is treated as a crucial request in an era of global energy and pollution crises. Following up on this hotspot trend, this paper examines the effectiveness of a modified optimization-based energy management strategy (OpEMS) for a dual proton exchange membrane fuel cells (dPEMFCs)-battery-ultra-capacitors (UCs)-driven hybrid electric vessels (HEVs). At first, the summed power of the dual PEMFCs is defined by using the equivalent consumption minimum strategy (ECMS). Accordingly, a map search engine (MSE) is proposed to appropriately split power for each FC stack and maximize its total efficiency. The remaining power is then distributed to each battery and UC using an adaptive co-state, timely determined based on the state of charge (SOC) of each device. Due to the strict constraint of the energy storage devices' (ESDs) SOC, one fine-corrected layer is suggested to enhance the SOC regulations. With the comparative simulations with a specific rule-based EMS and other approaches for splitting power to each PEMFC unit, the effectiveness of the proposed topology is eventually verified with the highest efficiency, approximately about 0.505, and well-regulated ESDs' SOCs are obtained. [ABSTRACT FROM AUTHOR]

This paper proposes an output feedback-based control for uncertain electro-hydrostatic systems (EHSs) to satisfy high output tracking precision under the influences of unknown mismatched and matched uncertainties and unstructured dynamical behavior. In this configuration, an extended state observer (ESO) is first employed to obtain unmeasured states and suppress the adverse effect of matched uncertainty. Meanwhile, the influence of unstructured dynamical behavior is approximated by employing a radial basis function neural network (RBFNN)-based technique. With the unmeasured states observed, matched uncertainty, and system dynamics compensated, the robust backstepping sliding mode control is accordingly established and the lumped mismatched uncertainty is then suppressed through disturbance observer-based adaptive law. Interestingly, the proposed control methodology requires only output feedback but can address the whole system dynamics. The stability of the closed-loop system is theoretically proven through a Lyapunov theorem and the effectiveness of the proposed methodology is demonstrated through comparative simulations. [ABSTRACT FROM AUTHOR]

This article proposes a novel real-time optimization-based energy management strategy (EMS) for proton membrane exchange fuel cell (PEMFC)-battery-supercapacitors-driven hybridized-electric tramways (HETs). The proposed algorithm is derived based on an enhanced extremum seeking (ES) algorithm, with a new equivalent state-of-charge (SOC) and a new adaptive co-state introduced. Thereby, optimized reference power for each power source can be distributed appropriately when using three components. The workability and prominent of the proposed technique are demonstrated through comparative simulations with fuzzy-rule-based EMS (FEMS) and equivalent consumption minimization strategy (ECMS) in two case studies: with and without considering the supercapacitors, as an important factor in the EMS design to stabilize the SOC of energy storage devices (ESDs). Briefly, under the proposed ES-based method, the PEMFC power can be regulated such that high-efficiency can be performed, approximately by 46.7%. Subsequently, the hydrogen consumption is reduced about 31.2% compared to a comparative fuzzy-based EMS. Besides, the supplements' SOCs at the end of a driving cycle are also regulated to be equal to the initial ones. [ABSTRACT FROM AUTHOR]

In recent years, reducing the energy consumption in a hydraulic excavator has received deep attention in many studies. The implementation of the novel independent metering valve system (NIMV) has emerged as a promising solution in this regard. However, external factors such as noise, throttling loss, and leakage have negative influences on the tracking precision and energy saving in the NIMV system. In this paper, a novel control method, simple but effective, called a neural network-fractional order-proportional-integral-derivative controller is developed for the NIMV system. In detail, the fractional order-proportional-integral-derivative (FOPID) controller is used to improve the precision, stability, and fast response of the control system due to the inclusion of non-integer orders in the proportional, integral, and derivative terms. Along with that, the auto-tuning algorithm of the neural network controller is applied for adjusting five parameters in the FOPID controller under noise, throttling loss, and leakage. In addition, the proposed controller alleviates the amount of calculation for the system by using model-free control. To verify the effectiveness of the proposed controller, the simulation and experiment are conducted on the AMESim/MATLAB and a real test bench. As a result, the proposed controller not only operates the NIMV system accurately in the target trajectory but also reduces energy consumption, saving up 23.33% and 29.25% compared to FOPID and PID in the experimental platform, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical energy control strategy for a hybrid dual fuel cell/battery tramway, combining online and offline optimization methods while considering the battery's dynamic behavior. In the upper layer, an online band-pass filter-based extremum-seeking control (BFESC) is employed to estimate the reference power between the dual fuel cell system and battery. In addition, the battery's dynamic behavior is considered a penalty function of the BFESC to maintain its parameters within the desired boundaries. In the middle layer, the power requirement for each fuel cell system is calculated by using an offline method called the map search method. Finally, the fuel cell and battery provide the required power to the DC bus through DC/DC converters, which are controlled by PID controllers in the lower layer. To verify the effectiveness of the proposed control strategy, a simulation model is built in Matlab/Simulink. The results demonstrate that the dual fuel cell/battery system under the control of the proposed energy management strategy (EMS) can operate efficiently while improving the battery's durability. The efficiency of the fuel cell system when using the proposed EMS was lower than 4% compared with the non-constraint EMS. However, the capacity loss of the battery could improve up to 25.9% in high-current and high-SOC cases. [ABSTRACT FROM AUTHOR]

The new configuration of independent metering valve (NIMV) system uses three proportional valves that gave been effectively proven to be energy saving compared with a conventional independent metering valve system in the fixed load condition. However, the variable load condition completely affects the accuracy and energy consumption during the operation of excavators. To improve the motion tracking precision and reduce the energy consumption of the NIMV system, a novel control method based on the coordinated control of the pump and the valve is proposed. In detail, the valve is controlled by considering velocity, load force, and position feedback of the cylinder. Meanwhile, velocity feedforward and position feedback methods are used to control the speed of the pump. In addition, a switching mode for the NIMV system is designed to flexibly select the metering modes based on the load and velocity conditions. To confirm the effectiveness of the proposed control method, the co-simulation model is built by using the AMESim and MATLAB software. From the results, the proposed method not only has high trajectory tracking precision with the displacement error of the cylinder at around 3.6% but also achieves up to 6.4% energy saving. [ABSTRACT FROM AUTHOR]

This paper presents an innovative powertrain design and an energy regeneration system for hybrid hydraulic excavators to reduce energy consumption and emissions. The proposed system is designed to maximize engine efficiency and make full use of the energy gained from boom and arm retraction. The powertrain features an innovative design that incorporates a continuously variable transmission (CVT), which drives the main pump. It enables precise control of both the engine's speed and torque, ensuring that the engine operates within the high-efficiency range. The energy regeneration system is applied to regenerate the potential energy of the boom and arm, which can be used to either charge the battery or directly supply power to the main pump. Moreover, an energy management strategy based on an equivalent consumption minimization strategy is used to distribute the power while offering maximum engine efficiency. When compared with the existing hybrid system and conventional system, the simulation results indicated that the proposed approach achieves energy-saving efficiencies of 16.9 % and 77.1 % , respectively, at high velocities and 22.25 % and 53.5 % , respectively, at medium velocities. This research signifies a promising advancement for sustainable and efficient hydraulic excavator operations. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to achieve the resonant behavior of a point absorber floating buoy type of Wave Energy Converter using direct drive power take-off system. The system has four main components: a frame; a buoy with a guiding shaft; a supplementary mass coupled with a linear generator and a variable stiffness structure. Firstly, the motion in the vertical direction of the buoy in the sea is converted to an oscillating motion of the supplementary mass. Next, the mass is coupled with a copper coil. The coil motion inside a magnetic wall induces an electrical current in the coil as a linear generator. Besides, a pair of pre-tension springs creates a negative stiffness phenomenon that acts on the motion of the mass and increases the performance of the system. Finally, a variable stiffness structure is installed to control the trajectory of the mass, it can increase the velocity of the mass motion thus the performance of the system is improved. Configuration and working principles of WEC were introduced, studied and analyzed. The mathematical model was presented to explain system behavior. The numerical simulation had been carried out to evaluate the operation of the system. The experimental test rig had been set up and implemented to verify the effectiveness of the proposed structure. • This paper proposes a new method of Wave Energy Converter using a direct drive power take-off system. • The novel variable stiffness mechanism (VSM) has been proposed and investigated. • The mathematical model and experimental test rig are built to validate the system performance. • The mass travels a distance that is longer than that of the excitation motion up to 6 times. • The ball screw and motor are controlled to increase the tension force of the springs and boost the motion of the sup-mass. [ABSTRACT FROM AUTHOR]

In this paper, a novel design of an energy regeneration system was proposed for recovering as well as reusing potential energy in a boom cylinder. The proposed system included a hydraulic pump/motor and an electrical motor/generator. When the boom moved down, the energy regeneration components converted the hydraulic energy to electrical energy and stored in a battery. Then, the regenerated energy was reused at subsequent cycles. In addition, an energy management strategy has been designed based on discrete time-optimal control to guarantee position tracking performance and ensure component safety during the operation. To verify the effectiveness of the proposed system, a co-simulation (using MATLAB and AMESim) was carried out. Through the simulation results, the maximum energy regeneration efficiency could achieve up to 44%. Besides, the velocity and position of the boom cylinder achieved good performance with the proposed control strategy. [ABSTRACT FROM AUTHOR]

By replacing conventional supplies such as fossil fuels or internal combustion engines (ICEs), this paper presents a new configuration of hybrid power sources (HPS) based on the integration of a proton-exchange membrane fuel cell (PEMFC) with batteries (BATs) and supercapacitors (SCs) for hydraulic excavators (HEs). In contrast to conventional architectures, the PEMFC in this study functions as the main power supply, whereas the integrated BAT–SC is considered as an auxiliary buffer. Regarding shortcomings existing in the previous approaches, an innovative energy management strategy (EMS) was designed using a new mapping fuzzy logic control (MFLC) for appropriate power distribution. Comparisons between the proposed strategy with available approaches are conducted to satisfy several driving cycles with different load demands and verify the strategy's effectiveness. Based on the simulation results, the efficiency of the PEMFC when using the MFLS algorithm increased up to 47% in comparison with the conventional proposed EMS and other approaches. With the proposed strategy, the HPS can be guaranteed to not only sufficiently support power to the system even when the endurance process or high peak power is required, but also extend the lifespan of the devices and achieves high efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a strategy for a fractional order fuzzy proportional integral derivative controller (FOFPID) controller for trajectory-tracking control of an electro-hydraulic rotary actuator (EHRA) under variant working requirements. The proposed controller is based on a combination of a fractional order PID (FOPID) controller and a fuzzy logic system. In detail, the FOPID with extension from the integer order to non-integer order of integral and derivative functions helps to improve tracking, robustness and stability of the control system. A fuzzy logic control system is designed to adjust the FOPID parameters according to time-variant working conditions. To evaluate the proposed controller, co-simulations (using AMESim and MATLAB) and real-time experiments have been conducted. The results show the effectiveness of the proposed approach compared to other typical controllers. [ABSTRACT FROM AUTHOR]

Construction machines are heavy-duty equipment and a major contributor to the environmental pollution. By using only electric motors instead of an internal combustion engine, the problems of low engine efficiency and air pollution can be solved. This paper proposed a novel energy management strategy for a PEM fuel cell excavator with a supercapacitor/battery hybrid power source. The fuel cell is the main power supply for most of the excavator workload while the battery/supercapacitor is the energy storage device, which supplies additional required power and recovers energy. The whole system model was built in a co-simulation environment, which is a combination of MATLAB/Simulink and AMESim software, where the fuel cell, battery, supercapacitor model, and the energy management algorithm were developed in a Simulink environment while the excavator model was designed in an AMESim environment. In this work, the energy management strategy was designed to concurrently account for power supply performance from the hybrid power sources as well as from fuel cells, and battery lifespan. The control design was proposed to distribute the power demand optimally from the excavator to the hybrid power sources in different working conditions. The simulation results were presented to demonstrate the good performance of the system. The effectiveness of the proposed energy management strategy was validated. Compared with the conventional strategies where the task requirements cannot be achieved or system stability cannot be accomplished, the proposed algorithms perfectly satisfied the working conditions. [ABSTRACT FROM AUTHOR]