Internal Combustion Generator Research Articles

Analysis of Energy Efficiency Parameters of a Hybrid Vehicle Powered by Fuel with a Liquid Catalyst

A notable trend in the modern automotive market is the increased interest in hybrid cars. Hybrid cars combine a standard internal combustion engine with an electric motor solution. Research into increasing the energy efficiency of a conventional unit while meeting increasingly stringent exhaust emission standards is becoming a key postulate in this matter. This article discusses an analysis of modifying the fuel used by hybrid vehicles using the example of a selected drive unit equipped with a spark-ignition engine. This effect was tested after the Eco Fuel Shot liquid catalyst was added to the fuel. The research process was carried out in two stages, as follows: in road conditions using the Dynomet road dynamometer; and on the V-tech VT4/B2 chassis dynamometer. Tests were carried out to replicate road tests with a catalytic additive in the fuel. A mathematical model was created and the following energy efficiency parameters of the hybrid vehicle were calculated: the torque of the internal combustion engine, electric motor, and generator; the rotational speeds of the internal combustion engine, electric motor, and generator; the power of the internal combustion engine, electric motor, and generator; the equivalent fuel consumption of the electric motor and generator; the fuel consumption of the internal combustion engine, electric motor, and generator; and the mileage fuel consumption of the internal combustion engine, electric motor, and generator. The results of the tests made it possible to identify the benefits of using the tested liquid catalyst on the operation of the drive system of the analyzed hybrid vehicle. This research will be of benefit to both the demand side in the form of users of this category of vehicles, and the supply side represented by the manufacturers of power units.

Advantages of plug-in hybrid electric vertical take-off and landing aircraft with hydrogen energy storage

Electric vertical take-off and landing (eVTOL) aircraft are becoming more and more attractive due to the improvements in electric road vehicles, and the mounting demand for new urban air mobility. As here discussed, due to the low specific energy density of batteries, hybridization of the propulsion system with fuel chemical energy storage and electricity production on board by either an internal combustion engine and generator, or fuel cells stack, appears to be a better avenue to deliver performance (cruise speed, range, and payload) than using only large and heavy batteries at least through 2030.

Simulation investigates on operation characteristics of free piston internal combustion generator

To study the influence of the free piston generator structure on its stable operation, this paper chose the combining mathematical and physical methods to build a simulation model to investigate the influence factors. According to the dynamic and thermodynamic equation, the mathematical model of the free piston internal combustion generator system was established. the simulation model was built with the help of MATLAB/Simulink software, and the validity of the model was verified. Based on this, the influences of ignition position and piston group mass on the operation characteristics of free piston generator were investigated. The simulation results show that the factors such as ignition position, piston group mass have significant effects on the compression ratio, cylinder pressure, maximum acceleration, etc. of the free piston generator, which provides a theoretical basis for the stable operation control of the free piston internal combustion generator.

Implementation of poultry waste disposal technology for energy and fertilizer production

The developed unit, which implements the technology of separation of raw materials into useful components by thermal destruction, makes it possible to obtain fuel synthesis gas, in which carbon monoxide (CO) and hydrogen (H2) predominate, suitable for use in internal combustion generators for generating electrical energy, as well as saturated ash potassium (K) and phosphorus (P) suitable as a fertilizer in agriculture.

Energy management for hybrid electric vehicles using rule based strategy and PI control tuned by particle swarming optimization algorithm

<span lang="EN-US">Recently, hybrid electric vehicles are increasingly being used to replace conventional vehicles. In this paper, a control methodology is designed that can reduce fuel consumption and improve the vehicle’s dynamic response. As the control unit based on this methodology consists of two levels, the first depends on the application of a rule-based strategy for energy management between the main components of the vehicle, and this strategy is based on a set of rules that are activated according to parameters such as vehicle speed and the battery <a name="_Hlk108852620"></a>state of charge (SOC) that control the activation/deactivation of the internal combustion engine (ICE), motor, and generator. This level also makes ICE operate at operation points with high efficiency, which is represented by the optimal operating line (OOL). The second level is called the low control level, and it consists of two proportional-integral (PI) controllers used to control the speed of each ICE and the motor to obtain the appropriate torque for both of them to drive the vehicle properly. The particle swarming optimization (PSO) algorithm is utilized to tune the parameters of the PI controllers. The obtained results have effectively minimized fuel consumption and improved the performance of the vehicle.</span>

Machine Learning-Based Vehicle Model Construction and Validation—Toward Optimal Control Strategy Development for Plug-In Hybrid Electric Vehicles

Advances in machine learning inspire novel solutions for the validation of complex vehicle models and spur an easy manner to promote energy management performance of complexly configured vehicles, such as plug-in hybrid electric vehicles (PHEVs). A constructed PHEV model, based on the four-wheel-drive passenger vehicle configuration, is validated through an efficient virtual test controller (VTC) developed in this article. The VTC is designed via a novel approach based on the least-square support vector machine and random forest with the inner-interim data filtered by the ReliefF algorithm to validate the vehicle model as necessary. This article discusses the process and highlights the accuracy improvements of the PHEV model that is achieved by implementing the VTC. The validity of the VTC is addressed by examining the PHEV model to mimic the characteristics of internal combustion engine, motor, and generator behaviors observed through the benchmark test. Sufficient simulations and hardware-in-loop test are employed to demonstrate the capability of the novel VTC-based model validation method in practical applications. The major novelty of this article lies in the development of a VTC, by which the vehicle model can be efficiently developed, providing solid framework and enormous convenience for control strategy design.

An Optimal Control Strategy for Plug-In Hybrid Electric Vehicles Based on Enhanced Model Predictive Control With Efficient Numerical Method

Advances in machine learning inspire novel solutions for the validation of complex vehicle models and spur an easy manner to promote energy management performance of complexly configured vehicles, such as plug-in hybrid electric vehicles (PHEVs). A constructed PHEV model, based on the four-wheel-drive passenger vehicle configuration, is validated through an efficient virtual test controller (VTC) developed in this article. The VTC is designed via a novel approach based on the least-squares support vector machine and random forest with the inner-interim data filtered by the ReliefF algorithm to validate the vehicle model as necessary. This article discusses the process and highlights the accuracy improvements of the PHEV model that is achieved by implementing the VTC. The validity of the VTC is addressed by examining the PHEV model to mimic the characteristics of the internal combustion engine, motor, and generator behaviors observed through the benchmark test. Sufficient simulations and hardware-in-the-loop tests are employed to demonstrate the capability of the novel VTC-based model validation method in practical applications. The major novelty of this article lies in the development of a VTC, by which the vehicle model can be efficiently developed, providing a solid framework and enormous convenience for control strategy design.

Mini-Mobile Machine With Electric Control

The article discusses a mini-mobile machine of hybrid type designed in the Raphael Dvali Institute of Machine Mechanics. Mini-mobile machine is an intermediate link between two-wheel tractor and mini-tractor. The machine uses an electric system of control, which enables smoothly starting and stopping of machine, its maneuverability with independent changing rotation frequency and rotation direction of wheels, machine movement in forward and backward direction and braking. The machine is controlled by an operator with electrical panel both remotely and as well as sitting on the machine, which frees the operator from doing the hard work. Placing the operator directly on the machine increases adhesion power, allowing the machine to perform heavy agricultural operations. The construction of the machine provides for its operation with one or two active axels and is designed to perform various agricultural works. The represented construction of mini-mobile machine by simple alteration enables to work with one or two axles, to change the location of aggregates and units placed in the machine, and to equip it by different hanging equipment and devices. Thus, it is possible to build up the mobile machine with cross-country capability of different kind and purpose. In addition, it must be noted that the hybrid type power installation with an internal combustion engine, generators and electric drives was used for the first time for mobile vehicles of small mechanization in agriculture.

Unit commitment optimization of a micro-grid with a MILP algorithm: Role of the emissions, bio-fuels and power generation technology

Management strategies of complex energy systems composed by different technologies is mandatory to exploit optimally the characteristics of each power generator, to reduce the cost of energy, the impact of greenhouse gases emissions and to increase the penetration of mini- and micro-grids into energy systems. To this purpose, optimization methods and algorithms have to be developed to assess the unit commitment of generators and to suggest decision variables in the definition of the emission costs. In this paper, a novel Mixed Integer Linear Programming (MILP) optimization algorithm has been developed to compute the optimal management of a micro-energy grid composed either by four Internal Combustion Generators (ICGs), or three ICGs and a Micro Gas Turbine (MGT). The algorithm optimizes a multi objective function that takes in consideration the total cost, the NOx and the CO2 emissions of the system, while setting some technological constraints, like start-ups and transients that are typically neglected. Moreover, different fuelling of the devices is evaluated. The model proved the importance of including an accurate model of the greenhouse gases emissions as they can significantly affect the optimization results. Furthermore, it proved to be very flexible and to be a proper basis to be adopted in more complex systems embedding energy storage devices and renewable energy systems.

Small Cogeneration Unit with Heat and Electricity Storage

A micro cogeneration unit based on a three-cylinder internal combustion engine, Skoda MPI 1.0 L compressed natural gas (CNG), with an output of 25 kW at 3000 RPM is proposed in this paper. It is a relatively simple engine, which is already adopted by the manufacturer to operate on CNG. The engine life and design correspond to the original purpose of use in the vehicle. A detailed dynamic model was created in the GT-SUITE environment and implemented into an energy balance model that includes its internal combustion engine, heat exchangers, generator, battery storage, and water storage tank. The 1D internal combustion engine model provides us with information on engine start-up time, actual effective power, friction power, and the amount of heat going to the cooling system and exhaust pipe. The catalytic converter was removed from the exhaust pipe, and the engine was always operating at full load; thus, engine power control is not considered. An energy storage system for an island operation of the entire power unit for a large, detached house was designed to withstand accumulated energy for a few days in the case of a breakout. To reach a low initial system cost, the possible implementation of worn-out battery packs toward emission reduction in terms of the second life of the battery is proposed. The energy and emission balance are carried out, and the service life of the engine is also discussed.

Comparison of Batteries and Pumping Hydro with PaTs as energy storage technologies for a micro-hybrid generation system: Multi-objective optimization through a MILP algorithm

Small-scale hybrid energy systems are often composed by different power production technologies and adopted in mini-grids. In this work, a Mixed Integer Linear Programming optimization algorithm has been developed to compute the optimal scheduling of a micro-grid constituted by Internal Combustion Generators (ICGs) and a Storage System that can be either a conventional battery storage system or a Pumping Hydro energy Storage (PHES) based on Pump-as-Turbines. The algorithm computes the optimal energy generation scheduling of the micro-grid, minimizing a multi-objective fitness function constituted by the total costs of the energy system and the total CO2 and NOx emissions. In particular, the emissions are modelled with varying trends depending on the ICG load and not with constant values, which represents a simplification that is often adopted but that can induce misleading results. Furthermore, the algorithm takes into account all the physical constraints related to the generators and the storage system, such as maximum and minimum power generation, ramp-up and ramp-down limits and minimum up and down-time. The two energy storage technologies are compared and results show that a management strategy based on this algorithm can reduce significantly the total emissions of the system.

Towards a digital workflow to assess visual impact of solar modules and their operation within energy-hubs

This study proposes an integrated methodology to assess the BIPV potential of existing urban neighborhoods, including social acceptance and grid infrastructure management issues; as a demonstration, a case study in Geneva, Switzerland is considered. In particular, the annual solar radiation on the outdoor exposed areas is calculated on an hourly basis and converted into electricity by considering standard monocrystalline PV modules. Social acceptability is evaluated on a discrete qualitative scale, based on the average visibility of the building envelope from the public space and assessed through a psychophysically reliable indicator. Three different envelope surface coverage ratios are assumed for BIPV, i.e. for low, medium and high visibility respectively. Renewable electricity generation is used to match the hourly electricity demand for lighting, appliances as well as an air-to-air heat pump that covers heating and cooling needs. Excess electricity is used within multi energy hubs featuring PV panels, a battery bank and an internal combustion generator; as a last resort, electricity is injected to the grid. As such, the levelized cost of energy and the grid integration level can be calculated at each time step. The financial outcome of the analysis may be used to explore novel business models for solar energy renovations in urban contexts.

Redefining energy system flexibility for distributed energy system design

A novel method is introduced in this study to consider flexibility taking into account both system design and operation strategy by using fuzzy logic. A stochastic optimization algorithm is introduced to optimize the system design and operation strategy of the energy system while considering the flexibility. GPU (Graphics Processing Unit)-accelerated computing is introduced to speed up the computation process when computing the expected values of the objective functions considering a pool up to 5832 scenarios. Subsequently, a Pareto optimization is conducted considering Net Present Value (NPV), Grid Integration (GI) level (which represents the autonomy level of the energy system) and system flexibility. The case study assesses an energy system design problem for the city of Lund in Sweden. According to the obtained NPV and GI Pareto front, a renewable energy penetration level covering more than 45% of the annual demand of the energy hub (an integrated energy system consisting of wind turbines, solar PV panels, internal combustion generator and a battery bank) can be achieved. However, the flexibility of the system notably decreases when the renewable energy penetration level exceeds above 30%. Furthermore, the results show that poor system flexibility notably increases the risk of higher-loss of load probability and operation cost. It is also shown that the utility grid acts as a virtual storage when integrating renewable energy sources. In this context, a grid dependency level of 25–30% (of the annual energy demand) is sufficient while reaching a renewable energy penetration level of 30% and maintaining the system flexibility.

Detailed thermodynamic investigation of an ICE-driven, natural gas-fueled, 1 kWe micro-CHP generator

The purpose of this work is to record the baseline performance of a state-of-the-art micro-combined heat and power (mCHP) system. A second goal of this work is to provide detailed thermodynamic first and second law performance measurements of the internal combustion engine and generator subsystems. A global technology survey was conducted to identify the leading mCHP systems in the 1 kW electric range. The Honda ECOWILL was identified as the state-of-the-art system in the United States, and an unused unit was procured. The ECOWILL underwent round-robin performance testing at three independent laboratories. First law (energy) and second law (exergy) analyses were conducted on the steady state data. Analysis revealed the ECOWILL operated at a first law electrical efficiency of 23.5 ± 0.4% and a utilization factor of 74.5 ± 3.2%. The primary energy loss was heat transfer from the device, followed by chemical and thermal energy in the exhaust stack. The second law analysis showed the ECOWILL operated at a second law electrical efficiency of 23.1 ± 0.4% and total (including exergy in both the electrical and recovered waste heat streams) second law efficiency of 30.2 ± 2.3%. Key areas of exergy destruction were, in decreasing magnitude, heat transfer, combustion irreversibility, and generator and friction losses.

Optimum dispatch of a multi-storage and multi-energy hub with demand response and restricted grid interactions

Integrated energy systems such as multi energy hubs which combines different energy conversion technologies and storage is recently getting popular. These systems possess the potential to integrate distributed renewable energy sources with a minimum impact to the grid. Hence, a number of recent studies have focused on optimizing the operation of energy hubs with simple energy systems. This study focuses on optimizing the dispatch of a multi-energy hub model which includes solar PV (SPV) panels, wind turbines, boiler, Internal Combustion Generator (ICG), Cogeneration plant (CHP), energy storage (heat and electricity). The energy hub is considered to maintain limited interactions with the grid. Interactions with e-mobility is considered as a flexible demand. A detailed energy hub model is developed considering energy interactions among all the aforementioned components. Dispatch strategy is optimized using evolutionary algorithm. Results obtained from the evolutionary algorithm is compared with Particle Swarm Optimization (PSO) algorithm. A detailed analysis is conducted in order to assess the energy interactions within the system. Sensitivity of system components such as storage size, renewable energy capacity etc., grid interactions, and time horizon considered for optimization is subsequently assessed and reported concisely. Results obtained clearly shows choice of dispatch strategy is considerably volatile which makes the operation of the energy hub challenging. This can be mitigated up to a certain level by increasing the capacity of battery bank.

Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid

A paradigm change in energy system design tools, energy market, and energy policy is required to attain the target levels in renewable energy integration and in minimizing pollutant emissions in power generation. Integrating non-dispatchable renewable energy sources such as solar and wind energy is vital in this context. Distributed generation has been identified as a promising method to integrate Solar PV (SPV) and wind energy into grid in recent literature. Distributed generation using grid-tied electrical hubs, which consist of Internal Combustion Generator (ICG), non-dispatchable energy sources (i.e., wind turbines and SPV panels) and energy storage for providing the electricity demand in Sri Lanka is considered in this study. A novel dispatch strategy is introduced to address the limitations in the existing methods in optimizing grid-integrated electrical hubs considering real time pricing of the electricity grid and curtailments in grid integration. Multi-objective optimization is conducted for the system design considering grid integration level and Levelized Energy Cost (LEC) as objective functions to evaluate the potential of electrical hubs to integrate SPV and wind energy. The sensitivity of grid curtailments, energy market, price of wind turbines and SPV panels on Pareto front is evaluated subsequently. Results from the Pareto analysis demonstrate the potential of electrical hubs to cover more than 60% of the annual electricity demand from SPV and wind energy considering stringent grid curtailments. Such a share from SPV and wind energy is quite significant when compared to direct grid integration of non-dispatchable renewable energy technologies.

Biogas Technology in South Africa, Problems, Challenges and Solutions

Biogas is a gas that is produced from the biodegradation of organic materials. It consists mainly of methane and carbon dioxide. The biogas from anaerobic digestion can be a solution to South Africa’s energy problems. It can be used for electricity generation, cooking and as transport fuel. There are over 200 biogas digesters scattered across South Africa and the use of biogas is not growing fast in the country irrespective of its benefits in reducing energy related problems such as pollution and energy shortage. This paper reviews biogas technology in South Africa and highlights the problems, challenges and solutions to the expansion of the technology. The research was conducted by surveying biogas digesters installed in the country and measuring the biogas potential from selected digesters. The problems and challenges to biogas technology expansion in the country include; lack of research work on biogas technology, low efficiency of biogas as compared to conventional fuels such as diesel and petrol, cheap electricity cost from coal fired thermal power stations, large amounts of hydrogen sulphides in biogas that can cause corrosion to biogas pipes and internal combustion engines. It was highlighted that biogas digesters to be installed in the country should be sized in accordance with the availability of substrate. In addition, the calorific value of the biogas should be improved so that it can be used to fuel internal combustion engines and generator sets. It was also revealed that community based education on biogas production and its usage need to be initiated so as to reduce biogas digester failures. This would improve biogas technology expansion in the country.

Sizing and energy management of a medium hybrid electric boat

Fuel consumption is viewed as a fundamental problem in boats which are to operate on sea for a long time without need to refueling. In this paper, hybridization of a conventional medium-sized boat to reduce fuel consumption is considered. For this purpose, the optimal sizes for the main components, electric motor, internal combustion engine, and battery and generator are calculated via a constrained particle swarm optimization algorithm which considers accelerating and speeding expectations as the constraints. Furthermore, a new fuzzy-thermostat controller whose parameters are tuned via optimization is proposed to manage the energy flow between the main components. To estimate the fuel consumption, a backward–forward simulation approach based on the quasi-static maps of the diesel engine and electric motor is employed. Moreover, the boat resistance forces are calculated for a typical driving cycle at both displacement and planning modes. Simulation results reveal that hybridization of the conventional boat leads to a 40 % reduction in fuel consumption without violating the performance constraints.

A multi criterion analysis for renewable energy integration process of a standalone hybrid energy system with internal combustion generator

Integrating renewable energy into standalone Internal Combustion Generator (ICG) systems is an economical and eco-friendly option. However, previous studies demonstrate the difficulties in replacing the ICGs completely by using Solar PV (SPV) and wind energy with a dispatchable energy storage. This makes it interesting to analyze the limitations in integrating the SPV and wind energy into Hybrid Energy System. A multi criterion analysis is presented in this study, considering Levelized Energy Cost, Loss of Load Probability, and Fuel Consumption varying the scale of the ICG capacity to attain aforementioned objective. Changes in the system design with the integration of the SPV and wind energy were analyzed using Pareto multi-objective optimization considering Renewable Energy Capacity as an objective function. Sensitivity of the ICG capacity on optimum Renewable Energy Technology, role of the ICG in improving system reliability, etc., were subsequently analyzed. The results depict that the ICG capacity notably influence to the balance between wind and SPV capacity. An increase in the ICG capacity does increase the contribution from dispatchable energy source in most of the scenarios. Furthermore, it facilitates to amalgamate highly fluctuating renewable energy sources at a relatively low cost. This makes it inevitable to replace ICG with non-dispatchable renewable energy sources and energy storage.

Results of the development and testing of traction electrical equipment of mining dump truck with load capacity of 240 tons

Basic results of development of an ac electromechanical transmission for the BelAZ mining dump truck with a load capacity of 240 t carried out at Ruselprom have been considered. The requirements and features have been studied of traction electrical equipment that complicate the solved task, in particular the limited response speed of voltage control channel in a dc link, low capacity of the link, the range of control of variables with a field reduction of more than 15: 1, and required braking regime power twice exceeding the traction regime power. A functional diagram of traction electrical equipment is shown, and the frequency-dependent temperature derating of the extreme output current of the inverter to improve the reliability and maximum use of power keys is considered. The structures of control systems that work via excitation of a synchronous traction generator and by the left and right wheel drives and model of the dump truck have been described. As a result of modeling the dynamic characteristics and operating regimes of an internal combustion engine, generator and traction motors have been brought into coincidence, the most effective version of control algorithms in a slipping of the driving wheels has been selected, and the low sensitivity of electrical drives to the change of parameters of the power channel has been found. The program, the technique, and the results of tests of traction electrical equipment on a full-scale test bench have been presented. The required static indicators have been achieved, as well as the time of processing of the step rise of generator nominal load equal to 0.2 s with a voltage depression of 5% and a transition from the extreme traction torque to 90% of the brake torque of less than 2 s in any working speed. Ground tests of a dump truck with the designed set of equipment are planned for the first half of 2015.