The internal combustion engine is a widely used power equipment in various fields, and its energy utilization is measured using brake specific fuel consumption (BSFC). BSFC map plays a crucial role in the analysis, optimization, and assessment of internal combustion engines. However, due to cost constraints, some values on the BSFC map are estimated using techniques like K-nearest neighbor, inverse distance weighted interpolation, and multi-layer perceptron, which are recognized for their limited accuracy, particularly when dealing with distributed sampled data. To address this, an improved random forest method is proposed for the estimation of BSFC. Polynomial features are employed to increase higher dimensions of features for random forest by nonlinear transformation, and critical parameters are optimized by particle swarm optimization algorithms. The performance of different methods was compared on two datasets to estimate 20%, 30%, and 40% of BSFC data, and the results reveal that the method proposed in this paper outperforms other common methods and is suitable for estimating the BSFC map.

This paper studies an improved super-twisting sliding mode controller (IST-SMC) for the permanent magnet synchronous generator (PMSG) voltage loop to improve the anti-disturbance capability of the system. Compared to conventional voltage controllers, the control algorithm provides advantages in terms of system resistance to load disturbances. Conventional voltage controllers have significant voltage fluctuations and long recovery times during sudden load changes. To solve this problem, a voltage loop controller based on a super-twisting sliding mode (ST-SMC) is designed to enhance the immunity of the system. Also, the ST-SMC was improved to further increase the convergence rate of the system and enhance the dynamic performance. The convergence of the system away from the balance point is accelerated by introducing an exponential term, which in turn provides an improvement in the dynamic performance of the system. The effectiveness of the proposed control scheme was verified on a PMSG.

A marine variable speed generator can dynamically adjust the set speed of a diesel engine according to the actual power load level by the grading method, so the goal of energy conservation is achieved. However, the grading method relies on engineering experience. The actual range of power load fluctuation is uncertain, which leads to a decrease in fuel efficiency. Therefore, a method based on load sliding interval is put forward. In this method, a fixed width load interval is set at first, and then the interval slides on the diesel engine load at a step of 1%. The minimum fuel consumption rate speed for the interval is optimized during the sliding process. Finally, a minimum fuel consumption rate speed curve corresponding to the sliding interval position is obtained. The optimization objective is to have the minimum weighted average fuel consumption rate at the integer load points within each interval. The actual power load is monitored and used to determine the current load interval during the calculation of the set speed. The minimum fuel consumption rate speed curve optimized was applied to query the setting value of the diesel speed. The mean value engine model was applied for simulation under three load conditions. The results show that the sliding interval method could achieve the best fuel saving effect under any power load; the set value of the diesel engine speed changed smoothly under the fluctuating power load conditions, and the fuel saving ability was better according to the actual power load conditions on the ship.

Integrated power systems are gaining popularity in the field of power systems and DC integrated power systems are considered promising for electric propulsion ships due to their simple grid topology, low fuel consumption, and easy access to new energy sources. However, the dynamic response characteristics of the power plant can be compromised when a variable speed generator is used in a DC power system, despite achieving energy savings. In this research, we investigate the power control strategy of a specific type of a ferry’s DC power plant. We establish a mathematical model and a Matlab/Simulink-based simulation model to analyze the performance of the proposed strategy. The research utilizes the fast charging and discharging advantages of supercapacitor storage devices to compensate for the dynamic impact delay of the power output when using the variable speed generator set. Additionally, an improved DC bus voltage droop control method that incorporates voltage compensation is proposed to mitigate problems related to large bus voltage fluctuations under sudden load change conditions, enabling better load distribution between different power sources. The simulation results confirm the effectiveness of the proposed strategy in optimizing the speed-seeking method of the variable speed diesel engine sets matching with the supercapacitor, and its positive impact on the dynamic performance of the propulsion system is demonstrated under variable load conditions resulting from ferry operations.

This paper investigates the small-signal stability of a DC shipboard power system (SPS) with the integration of a supercapacitor. As an efficient energy storage solution, supercapacitors can not only provide rapid energy response to sudden power demand spikes, effectively mitigating load fluctuations, but also enhance the system’s resilience to disturbances. In the context of the parallel operation of two Permanent Magnet Synchronous Generators (PMSGs), the inclusion of supercapacitors may alter the system’s dynamic behaviors, thereby affecting its small-signal stability. This paper develops the small-signal model of SPS and explores the small-signal model under various power distribution strategies in the parallel operation of diesel generator sets. Through the calculation of eigenvalues and influence factors, the system’s oscillation modes are analyzed, and key parameters affecting the stability of the DC distribution system are identified. Furthermore, this paper meticulously examines the specific impacts of electrical and control parameter variations on the system’s small-signal stability. Simulation experiments validate the accuracy of the small-signal stability analysis after supercapacitor integration into SPS.