Engine Control System Research Articles

BLDC Motor speed control with dynamic adjustment of PID coefficients: Comparison of fuzzy and classic PID

Brushless DC (BLDC) motors, which have small volumes, are widely used in many areas from the aviation industry to industrial applications due to their high efficiency and torque. In parallel with the development of technology, the field of use continues to expand with the development of BLDC engine (BLDCM) control strategies and the decrease in control costs. In this thesis study, it is aimed to minimize the observed changes in rotor speed compared to the reference speed. To achieve this, PID parameters were tried to be changed simultaneously with fuzzy control techniques, taking the error value as a reference. The control system of the BLDC engine was designed in the MATLAB/Simulink environment. In the simulation, the operating stability of classical PID and PID with updated fuzzy-based parameters on two engines with the same features was compared at different speeds. As a result of the research, it was concluded that the correction of the speed observed in the rotor of the PID-controlled motor, whose fuzzy logic-based coefficients were updated, based on the reference speed was more stable and the percentage of exceedance for the reference value was lower, compared to the classical PID controlled motor.

Laboratory Equipment for Modeling, Analysis, Design, and Implementation of Control Systems in Engineering

Laboratory Equipment for Modeling, Analysis, Design, and Implementation of Control Systems in Engineering

Multi-channel gas-diesel engine control system based on jet-convective sensors

Accurate measurement of the dynamic flow rate of the components of the gas-fuel mixture is required in electronic automatic control systems of the internal combustion engine. The paper substantiates the structural construction of the measurement channels of the multi-channel gas-diesel engine control system. In the implementation of the measurement channels, special attention is paid to the structure of the jet-convective channel for obtaining an informative signal on the gas fuel flow rate and the structure of the ion-labeled channel for measuring the air flow rate. Application of jet-convective transducers is supplemented by the original structural scheme of primary signals processing, which will allow expanding the measurement range towards low flow rate values, increasing the speed and reducing the random component of the error.

Дослідження шляхів підвищення оперативності виконання діагностичних операцій електронних систем автотракторної техніки

The purpose of this study is to find ways to reduce production time spent on diagnostic operations during maintenance or repair of electronic control systems (ECS) in automotive vehicles. Existing methods of diagnosing engine control systems in vehicles are sufficiently effective, but in most cases, they require highly skilled personnel, the use of additional complex and expensive equipment, prolonged service cycles, which in turn increases the complexity of maintenance, and also does not provide for prior prediction of faults and system failures. Analysis of scientific publications has shown that to reduce the time for maintenance and repair of electronic systems, it is necessary to predict the residual life of ECS components in vehicles during maintenance, to further reduce the labor intensity of diagnostics and current repairs. In other words, diagnostics performed during maintenance or repair should include predicting the residual life of electronic system components. For the most critical ECS components in vehicles, it is proposed to apply a strategy of replacing them upon reaching a certain mileage, rather than upon failure. This organization method will reduce vehicle downtime in repair and reduce the time to troubleshoot ECS component failures. A method has been proposed for identifying design elements that limit the reliability of the ECS, taking into account the degree of influence of their failures on the engine's technical and economic characteristics and the cost of restoring its performance. The availability of such information is the basis of the ECS maintainability support system. An algorithm has been developed to search for hidden faults in the components of ECS subsystems, which includes predicting the failure of ECS components. This will help reduce the labor intensity of diagnostic operations during maintenance and repair.

Performance seeking control method for minimum pollutant emission mode for turbofan engine

The research shows that the impact of aero-engine pollutant emission on the environment cannot be ignored. In addition to fuel type and combustor structure, aero-engine exhaust pollutants are also related to engine operating conditions and control systems. In this context, taking CO and NOx as the main exhaust pollutants of the engine as the research object, a performance optimization control method of the minimum pollutant emission mode of the engine is proposed. Firstly, the CO and NOx emission characteristics of the engine under different operating conditions at sea level are calculated by CFD numerical simulation method, and the engine component-level model applicable to all flight envelope and all conditions is established according to the characteristic data. Secondly, in order to improve computational efficiency, an airborne model with high accuracy and real-time performance is established through the deep neural network. Compared to the component-level model, the average relative error of each performance parameter is less than 0.5 %, and the real-time performance is improved by about 12 times. Finally, the optimization principle of the minimum pollutant emission mode is discussed. The feasible sequential quadratic programming (FSQP) algorithm is selected, and the fuel quantity and throat area of the tail nozzle are taken as control variables. Numerical simulations are performed in the typical mission envelope. Simulation results show that the CO emission index decreases by 5 % and the NOx emission index decreases by more than 6.5 % through performance optimization control of the minimum pollutant emission mode under the premise of ensuring constant engine thrust and meeting other constraints.

Design and implementation for the state time-delay and input saturation compensator of gas turbine aero-engine control system

In order to obtain desired steady-state and transient performance of a gas turbine aero-engine during its operation, a usual way is to control the engine to operate in a manner close to its physical limits. The thermodynamic performance of a gas turbine aero-engine varies greatly within a wide working envelope, affected by factors such as engine performance degradation, actuator response lag and combustion time-delay. When the engine works in extreme conditions, for example rapid acceleration, some phenomena such as over-speed, over-temperature and over-pressure may occur. For this reason, various restrictions are often set in the engine control system to ensure safety during its operation, which are often realized by the form of saturation. In this paper, a compensation structure for gas turbine aero-engine state time-delay and input saturation is proposed. At first, the problems frequently occurred in the gas turbine aero-engine control system are investigated. And the gas turbine aero-engine control model is derived based on a thermodynamic non-linear model and its linearization model is established, together with its designed compensation structure. Differing from the existing technologies, a combination of dynamic system input saturation feedback and static state time-delay feedback is adopted in the proposed model. Then, the saturated nonlinearity and time-delay characteristic are introduced as convex combinations in the stability analysis. The local stability conditions of the closed-loop system are obtained by using Lyapunov–Krasovskii functionals and linear matrix inequalities (LMIs). Finally, hardware-in-loop (HIL) experiments are conducted to verify the feasibility of the proposed compensation method.

Design of Power Supply for Distributed Aero-engine Intelligent Control System

Compared with centralized power supply system architecture, distributed power supply architecture can better meet the requirements of distributed aero-engine intelligent control systems. The design of distributed power supply topology plays a vitally important role in the distributed power supply system. The paper presents an engineering design method of distributed power supply for the distributed control system in a certain aero-engine. The distributed power supply topology is developed. Based on this topology, the bus voltage level and the current of the distributed intelligent nodes are designed. The optimal selection method of transmission cable types between intelligent nodes is also provided based on the equivalent circuit of a distributed power supply system. The results show that the cable transmission loss and voltage drop meet the design specifications of electrical cable. The proposed distributed power scheme for the distributed engine control system results in minimal modifications, smaller transmission current, and lighter cables.

Artificial Intelligence (AI) Techniques for Intelligent Control Systems in Mechanical Engineering

In mechanical engineering, control systems are essential to the dependable and effective operation of mechanical equipment and processes. The advantages of integrating AI into control systems include energy savings, greater product quality, increased process effectiveness, and adaptive and predictive control. Various AI approaches, including machine learning methods like decision trees, neural networks, and support vector machines, are extensively studied for system identification, modelling, and adaptive control. AI techniques enhance these applications' control performance, energy efficiency, problem discovery, and maintenance. The methodology uses metaheuristic techniques for creating intelligent control systems, such as simulated annealing, ant colony optimisation, and harmony search. With the help of these algorithms, the solution space is efficiently searched for ideal control strategies while avoiding local optima. The importance of evaluating the learned control algorithm on a different dataset or running experiments to determine its performance is also underlined. Performance assessment benchmarks for tracking error, settling time, overshoot, and energy efficiency are provided in the results section. This paper investigates the use of AI techniques in mechanical engineering intelligent control systems. The paper also offers areas for additional research in intelligent control systems and identifies research directions for future advancements.

Research on Hydrogen-Fueled Turbojet Engine Control Method Based on Model-Based Design

Due to the substantial disparities in physical attributes between hydrogen fuel and conventional fuels, the development of an efficient controller presents a formidable challenge. In this context, this paper delves into the utilization of a model-based design (MBD) methodology for the purpose of conceiving and enhancing control systems for hydrogen-fueled turbojet engines. The investigation commences by adopting an established physical model of a hydrogen-fueled turbojet engine and subsequently validates its performance through rigorous simulation exercises. Consequently, this research undertakes a systematic deconstruction of the design process into discrete sub-phases, thus facilitating a seamless progression from system requirement analysis to system verification. This approach engenders a concurrent design and optimization of the control system. The ultimate confirmation of the controller’s efficacy and reliability is achieved through exhaustive simulations and Hardware-In-the-Loop testing. The research findings not only serve to augment design efficiency and mitigate design expenditures, but also propose avenues for further performance ameliorations in the realm of hydrogen-fueled turbojet engines. The control system accuracy of MBD is compared with the experimental results, and under high hydrogen fuel flow conditions, the errors reach an extremely low level of 0.1%. This affords a novel design paradigm within the domain of aero-engine control.

Evaluation of a pressure sensing glow plug in terms of its application possibility to control the combustion process of a hydrogen-powered spark-ignition engine

The article contains the results of an analysis of the suitability of a pressure sensing glow plug for use in a hydrogen engine control system. Due to the properties of hydrogen, the process of its combustion in spark-ignition engines is significantly different from the classic fuels. It is planned to use the pressure sensor signal to control the combustion process to obtain high power and efficiency, with the lowest possible emission of nitrogen oxides, which is the main harmful component of hydrogen engines. After an initial assessment of suitability, it was decided to use a pressure sensing glow plug. This choice is dictated by the low price, good availability and high durability of these sensors. The preliminary tests were carried out using a low-power single-cylinder SI engine coupled with a 48V generator. The tests were carried out for several values of engine speed and load of the generator and for classic gasoline with a research octane number (RON) of 95. In order to obtain an increased pressure rise rate in the cylinder, as for hydrogen fueling, the engine operation was also tested with unmodified light gasoline used as solvent, which is characterized by a significantly lower RON value. The use of a reference pressure sensor in the cylinder made it possible to determine the behavior of the PSG in various operating conditions. The tests revealed that the differences in the pressure waveforms registered with both sensors can be systematized depending on the engine speed and its load.

Design of mode transition control system for tandem TBCC engine based on direct performance parameters closed-loop control

Abstract This paper conducts a study on closed-loop control of engine performance parameters during mode transition process of TBCC engine based on artificial intelligence method. Firstly, a composite modeling method based on stepwise regression analysis and batch normalization-depth neural network is proposed to establish the on-board model during mode transition to estimate the thrust and inlet airflow in real-time. Secondly, based on the hybrid penalty function-particle swarm optimization algorithm, a mode transition control schedule applicable to the closed-loop control of thrust and inlet airflow is developed. Finally, a data processing method based on similarity conversion is proposed to extend the applicable envelope range of the mode transition control system. The transition time is shortened by 33.3 %, and the fluctuations of thrust and inlet airflow are reduced by 1.33 % and 10.77 %, respectively. When the control system is applied to the off-design mode transition process, a satisfactory mode transition performance is also obtained.

Develop an ECU for Controlling Fuel Injectors Using Arduino and LabVIEW for Training Purposes

The technology of electronic motor control is now advancing rapidly. Many studies and applications have been done on automatic system control in vehicles. The automatic fuel injection control system for automobile engines is a unique area of study and instruction in universities. The engine will run more efficiently, use less fuel, and emit fewer emissions when the fuel injection system is precisely controlled. It is challenging for student research to evaluate improvements to engine performance on real engine controller units (ECUs). Since their ECUs are already set for specific automotive duties, it is challenging to run tests by modifying the ECU's input parameters. In this study, a programmable ECU was created to explore the characteristics of the fuel injection system using the open-source, low-cost Arduino microcontroller. Using LabVIEW software, the algorithmic program computes and graphically simulates the injector characteristics. This study determines the injector opening time and fuel volume injected using the data from the intake manifold pressure sensor, lambda signal, engine temperature, throttle position, engine speed, and exhaust gas sensor. The primary objective of this study was not to replace a real ECU. It was more beneficial for students to be able to equip themselves with tools and apply methodologies to perform many experiments at home rather than utilizing commercially available ECUs at exorbitant rates, thanks to the development of a low-cost ECU based on Arduino and LabVIEW in this study.

Ринок та перспективи газотурбінних двигунів для важких транспортних гелікоптерів

The subject of this study is the current state of the market and prospects for the development of heavy transport helicopters and their power plants. This article provides a classification of helicopters and a segment of medium-heavy and heavy helicopters with gas turbine engines. The field of application of such helicopters is briefly described. The purpose of this article is to evaluate the activities of Element JSC in the field of developing electronic control systems for gas turbine engines for heavy class helicopters. Such systems for Element JSC, in particular, are RDTs-2500 and RDTs-450M-117B units for TV3-117VMA-SBM-1B series turboshaft engines, created by Motor Sich JSC. Objective: To provide information on the main types of heavy helicopters manufactured and operated today, as well as a description of the gas turbine engines installed on these helicopters. The field of application of such helicopters is briefly described. The segment of heavy helicopters with gas turbine engines is the largest in terms of money on the world market of civil helicopters, and the forecast of deliveries of such helicopters for the next 5-7 years is given. Most helicopter models are not completely new developments, but have been improved over many years. Characteristic design features of heavy helicopters with gas turbine engines, features of the arrangement of units and equipment are given. The main structural and structural features of gas turbine engines of various manufacturers and the types of helicopters on which they are installed are given. Brief information on Russian and Ukrainian gas turbine engines - VK-2500 and TV3-117VMA-SBM-1B is provided separately. The results. Despite the active development of eVTOL technologies in the sector of small rotorcrafts, the development and improvement of gas turbine engines continues. Heavy helicopters of both traditional and non-traditional designs are being developed. Conclusions. Modernization of the design and "remotorization" of the Mi-8 helicopter is a good opportunity for "Motor-Sich Helicopters", but it needs its own developments. Many promising Ukrainian developments were canceled due to the war. Analysis of the technical characteristics of TVaD for heavy helicopters shows that domestic engines are almost in no way inferior to their European and American competitors. Promising TVaD of SE "Ivchenko-Progress" AI-130 with a capacity of 3,000 hp. can become an even more attractive proposition.

Формування математичної моделі турбовального двигуна

The subject of the study is the process of forming a mathematical model (MM) of a turboshaft gas turbine engine and a twin-engine helicopter power plant, which provides the determination of parameters of the working process in steady and transient operating modes for use in the estimation of dynamic characteristics, in the analysis and synthesis of engine and helicopter automatic control systems. The goal is to substantiate the structure and methodology of MM formation intended for use in real and accelerated time scale systems. Tasks: implementation of the previously proposed MM structure taking into account the turboshaft engine performances, development of a methodology for determining the MM coefficients based on known information about the static and dynamic properties of the engine, and formation of the MM structure of a two-engine helicopter power plant. For this, the methods of the theory of airjet engines and the theory of linear dynamic systems are used. The following results were obtained: the structure of a multimode high-speed MM of a turboshaft engine and a two-engine power plant was formed and tested. The scientific and practical novelty of the obtained results is as follows: the structure of the multimode linearized MM of the turboshaft engine is formed, which consists of static and dynamic submodels implemented in corrected parameters; the modeling technique was worked out on a simplified model, compiled considering expert information about the static and dynamic properties of the engine in the considered operation area. Formulas were obtained that relate the coefficients of the linear dynamic model to the values of the time constants of the rotors and the sensitivities obtained from the static characteristics; transient characteristics of the engine based on changes in fuel consumption and load power are determined, which correspond to physical knowledge about the engine; the modeling methodology and MM structure of a two-engine power plant were formed, which is distinguished by the combination of individual static and linear dynamic models of two engines with a single nonlinear dynamic model of the helicopter rotor; a simplified MM load necessary for testing the MM of the engine installation is proposed, which provides the calculation of the power consumed by the rotor, depending on the angular position of the blades.

Формування динамічних моделей газотурбінних двигунів для використання в системах автоматичного керування та контролю

The subject of the study is the process of forming a mathematical model (MM) of an aviation gas turbine engine, which provides the calculation of parameters of the work process in stable and transient operating modes for use in the evaluation of dynamic characteristics, in the analysis and synthesis of automatic engine and aircraft control systems, as part of aviation simulators, and in on-board control and diagnostics algorithms. The goal is to substantiate the structure and methodology of MM formation, intended for use in real and accelerated time scale systems. Task: formulation of requirements for MM, substantiation of the interaction between static and dynamic submodels, substantiation of the composition of arguments and the way of considering the influence of external conditions, as well as the position of the elements of the mechanization of the gas flow duct. For this, the methods of the theory of airjet engines are used. The following results were obtained: the requirements for MM of aircraft gas turbine engines designed to solve the problems of engine and aircraft control were formulated, and the structural forms of MM were substantiated, which ensure high accuracy of modeling with minimal complexity and the possibility of real-time implementation. The scientific and practical novelty of the obtained results is as follows: the requirements for dynamic MM of aircraft engines have been summarized, the problems of structural implementation and combination of static and dynamic submodels, the rational selection of their input parameters and considering the influence of external conditions on static and dynamic characteristics have been analyzed, the software implementation of MM in in the Matlab Simulink environment of a two-shaft turbofan engine and compared the simulation results obtained using the developed simplified MM and the original nonlinear thermo-gas-dynamic model based on the solution of the joint operation equations of components. It is shown that in the working range of modes, the MM error does not exceed 5%, the dynamic errors of the rotor rotation frequencies are less than 4%, the compressor pressure and gas temperature are less than 7%, or the thrust is less than 10%. Errors in estimating the duration of acceleration and deceleration of the engine are within 0.2...0.6 s.

Turbo-shaft engine adaptive neural network control based on nonlinear state space equation

Intelligent Adaptive Control (AC) has remarkable advantages in the control system design of aero-engine which has strong nonlinearity and uncertainty. Inspired by the Nonlinear Autoregressive Moving Average (NARMA)-L2 adaptive control, a novel Nonlinear State Space Equation (NSSE) based Adaptive neural network Control (NSSE-AC) method is proposed for the turbo-shaft engine control system design. The proposed NSSE model is derived from a special neural network with an extra layer, and the rotor speed of the gas turbine is taken as the main state variable which makes the NSSE model be able to capture the system dynamic better than the NARMA-L2 model. A hybrid Recursive Least-Square and Levenberg-Marquardt (RLS-LM) algorithm is advanced to perform the online learning of the neural network, which further enhances both the accuracy of the NSSE model and the performance of the adaptive controller. The feedback correction is also utilized in the NSSE-AC system to eliminate the steady-state tracking error. Simulation results show that, compared with the NARMA-L2 model, the NSSE model of the turbo-shaft engine is more accurate. The maximum modeling error is decreased from 5.92% to 0.97% when the LM algorithm is introduced to optimize the neural network parameters. The NSSE-AC method can not only achieve a better main control loop performance than the traditional controller but also limit all the constraint parameters efficiently with quick and accurate switching responses even if component degradation exists. Thus, the effectiveness of the NSSE-AC method is validated.

Unsteady Heat Transfer of Pulsating Gas Flows in a Gas-Dynamic System When Filling and Emptying a Cylinder (as Applied to Reciprocating Machines)

The thermal and mechanical perfection of the processes in the gas exchange system during the filling and emptying of the cylinder makes it possible to increase the productivity and efficiency of reciprocating machines for various purposes. The study was designed to obtain experimental data on the local heat transfer of pulsating flows in the intake and outlet pipelines of a piston engine model, their analysis, and mathematical description. The scientific novelty of the study is as follows: (1) the patterns of change in the local heat transfer coefficients of pulsating gas flows in the inlet and outlet pipelines for the piston engine model were obtained for the first time; (2) a mathematical description of the experimental data on local and average heat transfer in the inlet and outlet pipelines is proposed. The physical features of the change in the rate of heat transfer in the intake and exhaust systems for a full engine cycle are discussed. A spectral analysis of the harmonic functions of the change in the local heat-transfer coefficient in gas exchange systems is performed. A set of mathematical dependencies of changes in the local and average heat-transfer coefficients of flows in the inlet and outlet pipelines on operation factors are presented. These data can be used to assess the quality of filling and cleaning the cylinder, determining thermal stresses in the details of gas exchange systems, developing devices for using exhaust gas energy, creating engine control systems, and so on. Moreover, the results obtained can be used to adjust (and test) mathematical models, as well as refine engineering methods for calculating gas exchange processes in reciprocating machines for various purposes.

A State Estimation Method for Multisensor Uncertain Systems Based on Sequential Fusion and Zonotope

Most actual multi-sensor systems are usually affected by unexpected distractions such that the probability distributions of noises may become unforeseeable. For the classical state estimation methods, if the probability distributions of noises are not accurate, it will cause large estimation errors or even filtering performance divergence. Therefore, a fast and accurate measurement-sequence-fusion-zonotope (MSF-Z) state estimation method is proposed, which is the first attempt for multi-sensor sequential fusion to use only the boundary knowledge without using probability distributions of noises. The method firstly gives a family of zonotopes containing the intersection of the predicted state set and the measurement polytope, where all measurements are fused one by one according to their time sequence arriving at the fusion center, which improves the real-time performance, meanwhile, the dimension of the output matrix is reduced, which reduces the computational complexity. Then, find a zonotope with the smallest volume as the external description of the intersection. Next, obtain the compact set of the estimated state using the reduction operator to improve accuracy, which effectively solves the problem of multi-sensor state estimation when the probability distributions of noises are unknown. Finally, the simulation of a turbofan engine control system verifies that the proposed method has high accuracy and good time performance.

In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter.

Real-time estimation of the in-cylinder pressure of combustion engines is crucial to detect failures and improve the performance of the engine control system. A new estimation scheme is proposed based on the Extended Kalman Filter, which exploits measurements of the engine rotational speed provided by a standard phonic wheel sensor. The main novelty lies in a parameterization of the combustion pressure, which is generated by averaging experimental data collected in different operating points. The proposed approach is validated on real data from a turbocharged compression ignition engine, including both nominal and off-nominal working conditions. The experimental results show that the proposed technique accurately reconstructs the pressure profile, featuring a fit performance index exceeding 90% most of the time. Moreover, it can track changes in the engine operating conditions as well as detect the presence of cylinder-to-cylinder variations.

Preparation and Analysis of Experimental Findings on the Thermal and Mechanical Characteristics of Pulsating Gas Flows in the Intake System of a Piston Engine for Modelling and Machine Learning

Today, reciprocating internal combustion engines are used in many branches of the economy (power engineering, machine engineering, transportation, and others). In order for piston engines to meet stringent environmental and economic regulations, it is necessary to develop complex and accurate control systems for the physical processes in engine elements based on digital twins, machine learning, and artificial intelligence algorithms. This article is aimed at preparing and analysing experimental data on the gas dynamics and heat transfer of pulsating air flows in a piston engine’s intake system for modelling and machine learning. The key studies were carried out on a full-scale model of a single-cylinder piston engine under dynamic conditions. Some experimental findings on the gas-dynamic and heat-exchange characteristics of the flows were obtained with the thermal anemometry method and a corresponding measuring system. The effects of the inlet channel diameter on the air flow, the intensity of turbulence, and the heat transfer coefficient of pulsating air flows in a piston engine’s inlet system are shown. A mathematical description of the dependences of the turbulence intensity, heat transfer coefficient, and Nusselt number on operation factors (crankshaft speed, air flow velocity, Reynolds number) and the inlet channel’s geometric dimensions are proposed. Based on the mathematical modelling of the thermodynamic cycle, the operational and environmental performance of a piston engine with intake systems containing channels with different diameters were assessed. The presented data could be useful for refining engineering calculations and mathematical models, as well as for developing digital twins and engine control systems.