This article investigates the steady-state performance of a closed-circuit hydrostatic (HST) drive using a variable displacement pump and a variable displacement motor where the speed of the drive is varied by controlling pump or motor. The drive is operated over a wide range of load torque and speed in two modes of operation: the pump controlled mode and the motor controlled mode. The efficiencies of the pump, motor, and the prime mover driving the pump are taken into account to analyze the overall performance of the drive. In this respect, considering various flow and torque losses of the HST drive components, the equations representing efficiencies of the drive are identified by comparing with the experimental data. The simulation is carried out using MATLAB. The results of the study may be useful to identify the control parameters of the drive to operate it at a reasonable efficiency zone.

The electrification of on-road vehicles has got momentum in recent years, but for Non-Road Mobile Machines there are still many barriers to cross. In order to completely eliminate the internal combustion engine or reduce its use, the energy loss in machines needs to be minimised at every possible section. One such part is the steering of heavy non-road mobile machines which has been unchanged to a large extent for decades, especially in articulated machines. The major cause of the industry being cautious in replacing the traditional steering system is its safety. As being a safety-critical system, it requires to comply with the highest safety standards. An articulated steered wheel loader has been selected as a case study in this article to first carry out a detailed hazard analysis to assess the machine performance levels required for steering. Two scenarios are selected for hazard analysis: 1. the wheel loader is on work site; 2. the wheel loader is travelling on road. To achieve the required performance level, the requirements of functional safety and safety integrity level of the steering are analysed. Based on corresponding standards and the required performance level for the steering, a new electro-hydrostatic-based steer-by-wire system is proposed. The proposed steering complies with safety standards for articulated steering and has the potential for energy saving. The simulation of the proposed system is carried out from an energy-efficiency point of view in MATLAB/Simulink. The proposed electro-hydrostatic steering system is compared to the traditional steering of a wheel loader in the Mevea digital twin environment and has been found to be substantially more energy efficient in the primary analysis. The simulations show that in conventional steering, 51% of energy is wasted in the steering valve alone, while in EHA (Electro-hydrostatic actuator) steering only 29% is wasted in the entire steering system.

The articulated Heavy Earth Moving Machinery predominantly use hydrostatic steering, because of its reliability and redundancy. In earlier studies an energy efficient Electro-Hydrostatic Steering System was proposed, which works on Steer-by-Wire principle and comply with the safety standards. This paper presents co-simulation of a wheel loader model with hazard-free Steer-by-Wire. A cosimulation model using three software platforms; Mevea for multibody dynamics and mechanics, Simcenter AMESim for hydraulics, and MATLAB/Simulink for hydraulics, control, and data analysis, is created to analyse the hazard-free functionality of the steering. The simulation model of primary steering, which is an electric motor controlled Electro-Hydrostatic Actuator, is validated experimentally. In these heavy machines, as required by the standards there shall always be a secondary steering system for redundancy. The secondary steering, which is through a proportional control valve is modelled using the characteristics of the commercial product. There are five possible hazard scenarios in steering application of such machinery, which have been identified by the authors in earlier publication. These five hazard scenarios are realised in co-simulation model by modelling the respective faults in the primary steering, and the effectiveness of the hazard-free functionality in the steering is analysed. The study demonstrates that the novel Steer-by-Wire for articulated steering can effectively mitigate the potential hazards associated with steering in Heavy Earth Moving Machinery, moreover, co-simulation model provides an effectual mean to analyse the novel solutions.

Electro-hydrostatic actuators (EHAs) are used in aerospace, industrial, and off-road applications due to their efficiency and self-contained operation. However, degradation of critical components, such as the pump, can lead to reduced performance and unexpected failures. Conventional control strategies often neglect real-time degradation effects, limiting their ability to optimize both actuator performance and remaining useful life (RUL). This study addresses this gap by developing a health-aware control (HAC) framework that integrates degradation modeling with predictive control for EHAs. The proposed HAC system incorporates a nonlinear Wiener degradation model to estimate internal leakage progression in the pump. The degradation state is estimated online using an extended Kalman filter (EKF) and integrated into a model predictive control (MPC) framework to dynamically adjust control actions based on degradation predictions. The effectiveness of the approach is evaluated through simulations, comparing it to a baseline PID-controller. The choice of MPC and EKF over traditional PID control is justified by their ability to handle nonlinearities, provide predictive capabilities, and offer robust state estimation. Simulation results show that the HAC system extends the RUL of the gear pump by 3.22 %, compared to the PID controller. The system successfully mitigates degradation effects, while maintaining an average position tracking error of 1.39 mm. Although the RUL improvement is modest under accelerated degradation conditions, the proposed approach shows strong potential for real-world applications where degradation occurs over extended periods. Future work will focus on experimental validation using physical test rigs and refining the degradation model to enhance prediction accuracy and control adaptability.

Electro-hydrostatic actuators are widely used in aerospace, industrial, and off-road machinery due to their efficiency and self-contained design. However, gear-pump degradation increases internal leakage, reducing performance and elevating failure risk. This paper proposes a health-aware control framework that accounts for pump degradation in closed-loop control. Internal leakage progression is modeled with a nonlinear Wiener process and the degradation state is estimated online with an extended Kalman filter. The degradation state is used within a nonlinear model predictive controller to adjust control actions using predicted remaining useful life. The approach is evaluated in nonlinear simulations and compared with a proportional–integral–derivative controller. Results indicate that the proposed controller mitigates leakage-induced performance loss and increases predicted pump remaining useful life by 2.75% while maintaining acceptable position tracking accuracy. Although the improvement is modest under accelerated degradation, the framework is suited to slowly evolving degradation and supports predictive maintenance of safety-critical actuation systems.

The articulated Heavy Earth Moving Machinery predominantly uses hydrostatic steering, because of its reliability and redundancy. In earlier studies, an energy efficient Electro-Hydrostatic Steering System was proposed, which works on the Steer-by-Wire principle and complies with the safety standards. In the proposed steering system, the redundancy of the steering is achieved by an electronically controlled proportional valve circuit that activates when a fault is detected in the steering operation. The detection of fault and activation of secondary steering is safety critical in the operation, failure of which may lead to a hazardous outcome. In this paper, an intelligent approach is taken to identify the fault in steering using pressure signals. Different algorithms based on machine learning and deep learning, namely bagged decision tree ensemble, multi-layer perceptron, and Gaussian kernel-based Naive Bayes classifiers are selected for this work. A real-time interactive co-simulation environment integrating the proposed electro-hydrostatic steering system is used for the study. Two fault scenarios corresponding to the major hazardous outcomes related to steering are carefully simulated to capture the fault conditions in steering, ensuring that the classifiers are trained on a diverse and representative dataset. Finally, an ensemble of all the trained classifiers is created and integrated into co-simulation model to detect the faults in real-time simulation, using probabilistic approach. The study demonstrates an effective use of artificial intelligence (AI) to ensure safety through redundancy in the Steer-by-Wire for heavy earth-moving machinery.