Energy management in biodiesel production

Biodiesel economics revolves around both private and public features. Success for an incentive for producers and consumers needs to be sufficient to take part in the marketing arena with the currently accessible alternatives in the private dimension. “Whereas in the civic aspect, success is described in terms of the community objectives that prompt government’s intercession (i. e. subsidies) and whether biodiesel will attain the public goals in a remunerative manner compared to other alternatives if the public assessment is highly preferred, but the market incentives are deficient, there will not be a possibility to produce the biodiesel. On the other hand, if market values generate strong dividends among producers and purchaser, but the social gains are very small, or the costs are extremely high compared to other alternatives, then the activity may not represent a better use of scarce public resources. Biodiesel has become more enticing to the world recently due to its environmental benefits and the fact that it is made from renewable resources. The production cost of biodiesel is the main barrier to commercialization of the product. In the absence of tax relief, there is an urgent need to explore alternative feedstocks for the production of biodiesel. Furthermore, Properties impact of biodiesel and its feedstock, Engine type and its operating conditions Additives are effected by the biodiesel type and production characteristics. Where Engine power is always affected by properties of biodiesel, especially in heating value, viscosity, and lubricity

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance

Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators Using PID-Driven Data Techniques

In this study, a method for optimizing membership function tuning for fuzzy control of robotic manipulators using PID-driven data techniques is presented. Traditional approaches for designing membership functions in fuzzy control systems often rely on the experience and knowledge of the system designer, which can lead to suboptimal performance. By utilizing data collected from a PID control system, the proposed method aims to enhance the precision and controllability of robotic manipulators through improved fuzzy logic control. A Mamdani-type fuzzy logic controller was developed and its performance was simulated in Simulink, demonstrating the effectiveness of the proposed optimization technique. The results indicate that the method can outperform conventional P control systems in terms of overshoot reduction while maintaining comparable transient response specifications. This research highlights the potential of the PID-driven data-based approach for optimizing membership function tuning in fuzzy control systems and offers valuable insights for the development and evaluation of fuzzy logic control in robotic manipulators. Future work may focus on further optimization of the tuning process, evaluation of system robustness under various operating conditions, and exploring the integration of other artificial intelligence techniques for improved control performance

Integrated Thermal Systems and Controls Modelling for AUTO Mode Simulation and Optimization

Virtual product development has become the preferred approach for vehicle A/C system development. The advantages provided by virtual modelling compared to traditional approach are accelerated development pace and reduced cost. The thesis focuses on virtual modelling of the A/C system on a SUV vehicle based on experimental data. A virtual model of the A/C system is constructed and calibrated in Simcenter Amesim. The model includes a vapour-compression refrigeration cycle and a cabin air model. The components are modelled and calibrated based on supplier data. The two thermal systems interact thermally at the evaporator level. The cabin air blower unit with a PI controller and a small DC motor is also modelled in MATLAB/Simulink. The virtual thermal model is able to simulate the cabin air temperature development during High Ambient AUTO mode drive cycle. The controlled DC motor system tracks reference speed to provide adequate air flow for the cabin. The virtual models can be used for A/C system and components performance analysis and optimization. The modelling process provides deeper understanding on thermal and control systems design

Hybrid Field Oriented and Direct Torque Control for Sensorless BLDC Motors Used in Aerial Drones

In this study, a sensorless hybrid control scheme for brushless direct current (BLDC) motors for use in multirotor aerial vehicles is introduced. In such applications, the control scheme must satisfy high-performance demands for a wide range of rotor speeds and must be robust to motor parameter uncertainties and measurement noise. The proposed controller combines field-oriented control (FOC) and direct torque control (DTC) techniques to take benefit of the advantages offered by each of these techniques individually. Simulation results demonstrate the effectiveness of the proposed control scheme over a wide range of rotor speeds as well as good robustness against parameter uncertainties within -5to + 10% for inductance and -5to + 5% for resistance parameters. The proposed hybrid controller is robust also against noise in voltage and current measurements. In order to verify the results from simulation, the proposed hybrid controller is implemented in hardware using the TI C2000 Piccolo Launchpad and TI BOOSTXL-DRV8305EVM BoosterPack. Testing is done with a Bull Running motor typically used in aerial drones. Testing experiments demonstrate that the hybrid controller reduces the rotor speed ripple when compared to DTC while operating in steady-state mode and decreases the response time to desired speed changes when compared to FOC

Upravljanje bezkolektorskim DC motorom s distribuiranim parametrima zasnovano na linearnom kvadratičnom regulatoru s konačnim horizontom

An optimal control theory for linear quadratic finite time horizon problem is presented and combined with distributed parameters model of the BLDC (BrushLess Direct-Current) motor. Method appropriateness for minimization of the phase current control error and energy delivered to the drive is proven. The paper focuses on finding the best weighting configuration of the objective function. Presented control strategy is performed and presented employing the numerical computations.U ovom radu je predstavljen problem optimalnog upravljanja modelom bezkolektorskog DC motora s distribuiranim parametrima zasnovan na linearnom kvadratičnom regulatoru na konačnom horizontu. Metoda je prikladna za minimizaciju regulacijske pogreške fazne struje i utrošene energije za pokretanje pogona. Fokus rada je na traženju najboljih koeficijenata funkcije cilja. Predstavljena strategija upravljanja je realizirana i validirana u simulacijama

Design Methodology for Heavy-Lift Unmanned Aerial Vehicles with Coaxial Rotors

This work presents a novel design methodology for multirotor Unmanned Aerial Vehicles (UAVs). To specifically address the design of vehicles with heavy lift capabilities, we have extended existing design methodologies to include coaxial rotor systems which have exhibit the best thrust-to-volume ratio for operation of UAVs in urban environments. Such coaxial systems, however, come with decreased aerodynamic efficiency and the design approach developed in this work can account for this. The proposed design methodology and included market studies have been demonstrated for the development of a multi-parcel delivery drone that can deliver up to four packages using a novel morphing concept. Flight test results in this paper serve to validate the predictions of thrust and battery life of the coaxial propulsion system suggesting errors in predicted flight time of less than 5 percent