Electric Hybrid Research Articles

Global Optimization-Based Energy Management Strategy for Series–Parallel Hybrid Electric Vehicles Using Multi-objective Optimization Algorithm

Global Optimization-Based Energy Management Strategy for Series–Parallel Hybrid Electric Vehicles Using Multi-objective Optimization Algorithm

Modeling, Simulation and Control Strategy Optimization of Fuel Cell Hybrid Electric Vehicle

This work represents the development of a Fuel Cell Hybrid Electric Vehicle (FCHEV) model, its validation, and the comparison of different control strategies based on the Toyota Mirai (1st generation) vehicle and its subsystems. The main investigated parameters are hydrogen consumption, and the variation of the state of charge, current, and voltage of the battery. The FCHEV model, which is made up of multiple subsystems, is developed and simulated in MATLAB® Simulink environment using a rule-based control strategy derived from the real system. The results of the model were validated using the experimental data obtained from the open-source Argonne National Laboratory (ANL) database. In the second part, the equivalent consumption minimization strategy is implemented into the controller logic to optimize the existing control strategy and investigate the difference in hydrogen consumption. It was found that the ECMS control strategy outperforms the rule-based one in all drive cycles by 0.4–15.6%. On the other hand, when compared to the real controller, ECMS performs worse for certain considered driving cycles and outperforms others.

Design and Fabrication of Solar Windmill

In recent era, research and development activities in the field of renewable energy, especially wind and solar, have been considerably increased, due to the worldwide energy crisis and high global emission. Wind turbines & Solar are becoming popular in the renewable energy world. The design of hybrid electricity generation system by utilizing both solar and wind renewable energy to the domestic household in the remote area and for many applications like beside railway tracks, railway stations, highways for power generation, and for charging of electrical vehicle. The primary goal of the project is to design and create a compact wind turbine and solar panel to be used as an efficient way to generate electricity anywhere. It is not possible to operate a horizontal axis wind turbine for domestic use. Because it can function in low wind conditions as well, the Savonius vertical axis wind turbine may be a preferable option. According to tests, hybrid systems are the best option for supplying "high quality" power.

Improving Sparrow Search Algorithm for Optimal Operation Planning of Hydrogen–Electric Hybrid Microgrids Considering Demand Response

Microgrid operation planning is crucial for ensuring the safe and efficient output of distributed energy resources (DERs) and stable operation of the microgrid power system. The integration of hydrogen fuel cells into microgrids can increase the absorption rate of renewable energy, while the incorporation of lithium batteries facilitates the adjustment of microgrid power supply voltage and frequency, ensuring the three-phase symmetry of the system. This paper proposes an economic scheduling method for a grid-connected microgrid that considers demand response and combines hydrogen and electricity. Based on the operating costs of renewable energy, maintenance and operation costs of nonrenewable energy, interaction costs between the microgrid and main grid, and pollution control costs, an optimization model for dispatching a hydrogen–electric hybrid microgrid under grid-connected mode is established. The primary objective is to minimize the operating cost, while the secondary objective is to minimize the impact on the user’s power consumption comfort. Therefore, an improved demand response strategy is introduced, and an enhanced sparrow search algorithm (ISSA) is proposed, which incorporates a nonlinear weighting factor and improves the global search capability based on the sparrow search algorithm (SSA). The ISSA is used to solve the optimal operation problem of the demand-response-integrated microgrid. After comparison with different algorithms, such as particle swarm optimization (PSO), whale optimization algorithm (WOA), sooty tern optimization algorithm (STOA), and dingo optimization algorithm (DOA), the results show that the proposed method using demand response and ISSA achieves the lowest comprehensive operating cost for the microgrid, making the microgrid’s operation safer and with minimum impact on user satisfaction. Therefore, the feasibility of the demand response strategy is demonstrated, and ISSA is proved to have better performance in solving optimal operation planning problems for hydrogen–electric hybrid microgrids.

Comprehensive Analysis of Power Systems for Hybrid Electric Vehicles

Now the pollution problem is becoming more and more serious, and the gas emitted by cars has seriously affected the environment. In order to reduce environmental pollution and Strength conservation and emission discount, sell the first-rate sustainable development of China's new electricity automobile industry, accelerate the development of vehicle strength, and the study of new energy vehicles is inevitable. New power vehicles are designed to use unconventional energy sources or indirectly use gasoline energy in a way that differs from conventional automotive internal combustion engines. The new power vehicle is the superior technology to complete the power control and driving of the vehicle which transcends the traditional technology and way. It is a vehicle with new technology as well as new structure. This paper mainly analyzes the energy conversion of hybrid electric vehicles, the advantages and disadvantages of the power system of hybrid electric vehicles, and also discusses the actual application of technology and the plate and management mode of power battery.

Experimental and Simulation Research on Heat Pipe Thermal Management System Coupled with Battery Thermo-Electric Model

The lithium-ion battery is widely used in the power system of pure electric vehicles and hybrid electric vehicles due to its high energy density. However, the chemical and electrochemical reactions generate a lot of heat. If the heat is not transferred through some refrigeration methods in time, it will lead to a rapid rise in the temperature of the battery. In this paper, an electric–thermal coupling model of a cylindrical Panasonic 21700 battery was proposed by using offline parameter identification method. Based on this model, a battery thermal management system using a heat pipe was established. The experimental results show that the model can simulate the actual performance of battery well. When the ambient temperature is 25 °C, the battery parameters change little and battery performance is better. The heat pipe battery thermal management system performs better than the non-heat pipe battery system in the discharge process, and can control the battery temperature well at low and high temperatures. Changing the refrigerant temperature can achieve a better thermal management effect under suitable ambient temperature conditions.

Analysis of a Solar Hybrid Electricity Generation System for a Rural Community in River State, Nigeria

This paper presents the technical and economic analysis of a solar–wind electricity generation system to meet the power requirements of a rural community (Okorobo-Ile Town in Rivers State, Nigeria) using the Renewable—energy and Energy—efficiency Technology Screening (RETScreen) software. The entire load estimation of the region was classified into high class, middle class, and lower class. Two annual electricity export rates were considered: 0.1 USD/KWh and 0.2 USD/KWh. The results from the proposed energy model comprising a 600 kW PV system and a 50 kW wind system showed that with a USD 870,000 initial cost and USD 9600 O&M cost, the annual value of the electricity generated was 902 MWh. The simple payback was 5.1 years with a net present value of USD 3,409,532 when 0.2 USD/KWh was used as the annual export rate instead of 10.8 years for simple payback and an NPV of USD 1,173,766 when 0.1 USD/KWh was used. Thus, there is a potential to install a wind–solar system with average weather conditions of 4.27 kWh/m2/d for the solar irradiance and 3.2 m/s for the wind speed at a 10 m hub height using a rate of 0.2 USD/KWh as the electricity export rate.

Hybrid Deep Learning-Based Grid-Supportive Renewable Energy Systems for Maximizing Power Generation Using Optimum Sizing

The hybrid electricity production idea is a technology designed to produce and use electrical energy from many sources as part of an integrated setup. The combined size and power maximization technique for grid-connected renewable energy systems is presented in this research. This study optimizes three distinct geographic locations with various wind and sun renewable energy input potentials. Convolutional neural networks with long short-term memory are designed to maximize electricity production while taking consumer load, demand, and weather conditions into account. The established technique emphasizes the significance of taking into account the concurrent optimization of sizing and power management. To find the hybrid power system building option with the optimum cost–benefit ratio, the Shuffled Shepherd Optimization Technique is used. The optimization analysis uses annual demand data, solar irradiation, and wind turbine power output with a 10-min precision. Investigations have been done into how the system’s various parts behave. The amount of PV panels, wind turbines, battery banks, and the capacity of the diesel generator, together with the error rate, are the best choice factors shown by simulation results for sizing and producing the electricity for hybrid energy system. The results support the proposed strategy’s potential for producing hybrid renewable power.

A Comprehensive Analysis of Online and Offline Energy Management Approaches for Optimal Performance of Fuel Cell Hybrid Electric Vehicles

The global impact of hybrid electric vehicles (HEVs) is exponentially rising as it is an emission-free and reliable alternative to fossil fuel-based vehicles that cause enormous negative impacts on the socioeconomic and environmental sectors. Fuel cell hybrid electric vehicles (FCHEV) have been widely considered in the latest research as an energy-efficient, environmentally friendly, and longer-range green transportation alternative. The performance of these FCHEVs, however, is primarily dependent upon the optimal selection of Energy Management Strategies (EMSs) adopted for optimum power split and energy resource management. This research reviews the latest EMS techniques presented in the literature and highlights their working principle, operation, and impact on the FCHEV performance and reliability. This research also highlights the challenges associated with the globalization of FCHEVs and recommends future work and research directions essential for optimal FCHEV performance and commercialization.

User’s perceptions of electric, hybrid, and fuel-powered vehicles in Iraq and Jordan

The shift towards the use of electric vehicles or hybrids has become one of the methods used to reduce the sources of pollution in many countries around the world. This study aims to understand drivers’ perceptions and concerns with regard to electric, hybrid, and fuel-powered vehicles in Iraq and Jordan. An online survey was conducted through emails, social media, and connections to Iraq and Jordan. The study included 1352 participants, 662 (49%) from Iraq and 690 (51%) from Jordan. The chi-square homogeneity test was used to analyze the data. The majority of participants from Iraq reported that they do not have electric or hybrid vehicles because of the lack of charging stations. Participants from Jordan reported that they do not have electric or hybrid vehicles because they feel that electric or hybrid vehicles are unreliable. An additional logistic regression analysis was carried out to determine significant predictors that influence the person’s choice of having friendly environmental fuel sources (electric or hybrid). Significant variables were found, such as country of region (Jordan and Iraq), gender, age group, car ownership, vehicle emissions, and climate change-related issues. The study identified regional, cost, performance, reliability, and environmental issues that affect people’s perceptions and concerns about diversifying fuel sources used for vehicles. Raising public awareness of the benefits and actively changing society’s perception, in the long run, requires an initiative that can be sustained constantly in society.

Thermal analysis of phase change material encapsulated li-ion battery pack using multi-scale multi-dimensional framework

Li-ion batteries are employed to propel Electric vehicles (EVs) and Hybrid Electric Vehicles (HEVs) into a clean and sustainable future. A battery pack experiences high heat generation under extreme and abusive conditions, which may lead to catastrophic thermal runaway. The present study proposes an efficient and economical Phase Change Material (PCM) based Battery Thermal Management System (BTMS) to avoid thermal runaway. A 3D simulation is performed on a single battery (1P1S) and a battery pack consisting of six batteries stacked in series (1P6S), with and without PCM, using the multi-scale multi-dimensional Newman, Tiedemann, Gu, and Kim (NTGK) model in ANSYS. The NTGK model analyzes the battery pack's discharge behavior and thermal performance. For PCM-based BTMS, the NTGK is coupled with the solidification and melting model. The effect of ambient temperature, discharge rate, and convective heat transfer coefficient on 1P1S and 1P6S battery packs with and without PCM is investigated under extreme and abusive conditions. The ambient temperature (Tamb) significantly impacts PCM selection and battery performance. The effective T­amb – PCM combinations are proposed for the optimal working of the battery pack. Under the extreme conditions of the fast-discharging rate, the PCM-based BTMS reduces the maximum battery temperature by 25.3 K and 19.5 K and improves the temperature uniformity by 5.3 K and 3.6 K at 5C and 4C discharge rates, respectively. Also, at Tamb of 300 K, the proposed PCM-based BTMS significantly reduces the maximum temperature by 60.4 K, 46 K, and 29.3 K when the external shorting resistance is 0.10, 0.15, and 0.25 Ω, respectively. The proposed cooling system averts the thermal runaway when external shorting is 0.10 Ω, and internal shorting is >0.1 μΩ. This research will be helpful in the further development of PCM-based thermal management systems for large-scale and commercial applications.

Hybrid Energy Storage Systems Based on Redox-Flow Batteries: Recent Developments, Challenges, and Future Perspectives

Recently, the appeal of Hybrid Energy Storage Systems (HESSs) has been growing in multiple application fields, such as charging stations, grid services, and microgrids. HESSs consist of an integration of two or more single Energy Storage Systems (ESSs) to combine the benefits of each ESS and improve the overall system performance, e.g., efficiency and lifespan. Most recent studies on HESS mainly focus on power management and coupling between the different ESSs without a particular interest in a specific type of ESS. Over the last decades, Redox-Flow Batteries (RFBs) have received significant attention due to their attractive features, especially for stationary storage applications, and hybridization can improve certain characteristics with respect to short-term duration and peak power availability. Presented in this paper is a comprehensive overview of the main concepts of HESSs based on RFBs. Starting with a brief description and a specification of the Key Performance Indicators (KPIs) of common electrochemical storage technologies suitable for hybridization with RFBs, HESS are classified based on battery-oriented and application-oriented KPIs. Furthermore, an optimal coupling architecture of HESS comprising the combination of an RFB and a Supercapacitor (SC) is proposed and evaluated via numerical simulation. Finally, an in-depth study of Energy Management Systems (EMS) is conducted. The general structure of an EMS as well as possible application scenarios are provided to identify commonly used control and optimization parameters. Therefore, the differentiation in system-oriented and application-oriented parameters is applied to literature data. Afterwards, state-of-the-art EMS optimization techniques are discussed. As an optimal EMS is characterized by the prediction of the system’s future behavior and the use of the suitable control technique, a detailed analysis of the previous implemented EMS prediction algorithms and control techniques is carried out. The study summarizes the key aspects and challenges of the electrical hybridization of RFBs and thus gives future perspectives on newly needed optimization and control algorithms for management systems.

Optimal battery management strategies for plug-in electric hybrid buses on routes including green corridors

Public transport is a cornerstone in the transition towards sustainable cities. Moreover, greenhouse gas emissions can be further reduced through powertrain electrification. In this context, plug-in electric hybrid buses emerge as a suitable and flexible solution. They can switch between an electric motor and a combustion engine during operation. An optimal electric drive assignment strategy allows achieving a high electric range and reduced tailpipe emissions. In this work, we look for optimal strategies for maximizing the distance traversed in electric mode and minimizing the total emissions, for real routes including green corridors where the combustion engine cannot be used. Contrary to existing works, this approach does not only focus on the improvement of the bus performance in terms of energy consumption, but also on the environmental benefits and livability of cities. This challenge is solved using two multi-objective state-of-the-art evolutionary algorithms, and a novel heuristic, GreenK. Two real- world scenarios are analyzed, namely bus routes M6 in Badalona, and 18 in Grudziadz. Results show a significant reduction in emissions of up to 21% with respect to the strategy found by GreenK, meaning 24 kg less pollutants emitted daily and over 22.5% electric range increase, compared to the currently deployed solution.

Battery Thermal Management: An Application to Petrol Hybrid Electric Vehicles

Battery thermal management systems (BTMS) in hybrid electric vehicles can be complex and heavy. They tend to increase energy consumption, leading to higher carbon dioxide emissions. In this study, a new approach was investigated for the potential use of four fuel components as coolants for direct liquid-cooled (LC)-BTMS, N-Pentane, N-Hexane, N-Butane, and Cyclo-Pentane. The performance of the fuel components was numerically analysed and CFD modelled using ANSYS Fluent software. Several meshing iterations of the lithium-ion battery (LIB) module were performed to conduct mesh independence check for higher accuracy and less computational time. The LIB module was simulated, in comparison to a free air convection (FAC)-BTMS as a benchmark, at three discharge rates (1C, 1.5C, 2C) for each of the inlet velocity values (0.1, 0.5, 1 m/s). Results show that FAC-BTMS exceeded the LIB module optimal operating temperature range (293–313 K) at 2C. On average, at the worst condition (lowest inlet velocity and highest discharge rate), all fuel components of the LC-BTMS were able to maintain the LIB module temperature below 288 K. That is at least 4.7% cooler compared to FAC-BTMS, which renders the new approach viable alternative to the conventional BTMS.

Improvement of Autonomy, Efficiency, and Stress of Fuel Cell Hybrid Electric Vehicle System Using Robust Controller

Among issues facing the transportation sector today is the limited autonomy of electric vehicles, which are highly reliant upon energy storage systems. Considering this issue as the current research gap, researchers seek to prolong vehicle dependability through renewable-free and sustainable energy that tackles negative environmental impacts. This research exploits the electric vehicle’s kinetic energy to improve its performance and reliability. It uses fuel-cell resources and supercapacitors hybridized with lithium-ion batteries, in addition to DC generators connected to front wheels that convert their rotations into energy contributing to the vehicle’s overall power balance. A state machine-based energy management strategy computes fuel-cell setpoint power, while a dual-loop structure uses a super-twisting controller for DC bus voltage regulation and recovery, in addition to tracking banks’ setpoint currents. A speed controller-based artificial intelligence is proposed to reduce power losses and enable accurate tracking of running trajectory to improve vehicle mechanisms. The simulation results using Matlab Simulink software proved the proposed vehicle’s feasibility by adopting the free kinetic energy of additional DC generators that provided 28% of its total power requirements, resulting in superior supply efficiency reaching 98%. Thus, the stress on FC and battery was minimized by 21% and 10%, respectively, in addition to reducing fuel consumption by 39%, so the vehicle autonomy was extended, and its reliability was enhanced and supported, as targeted.

Pengairan Sawah Tadah Hujan Gunakan Rekayasa Pompa Air Sistem Listrik Hybrid

Rainfed rice fields are agricultural areas whose irrigation systems depend on the rainy season. In the dry season, agricultural areas are not planted. The villagers make a living in the agricultural area. During the rainy season, some people cultivate crops, and during the dry season, some people turn to entrepreneurs or work in cities. This went on for years, and to deal with it, farmers built wells and used fossil fuel engines to pump the water. According to the case found in Duri Village, Slahung-Ponorogo District, the right technology is needed, namely hybrid electric water pump technology. A solution to the problem of irrigating rainfed rice fields. Engineering a solar power plant using hybrid electricity is an alternative option that can be implemented. Based on the results of the evaluation of this solar panel design, it produces 200 Wp of energy with an optimum voltage of 21.1 volts and a maximum current of 9.0 A. The optimum average solar cell voltage is 20.42V when it is hot and the charging voltage is 14.3V DC current. On cloudy days, the average voltage is 19.20 volts, and the charging voltage is 13.60 volts. Sunlight capacity is 8 hours per day, with normal full exposure of about 5 hours/day. Based on the review of the findings, it is necessary to increase the power supply capacity to a greater extent.. fossil fuel engines, water pump technology

Experimental and numerical investigation of the impact of the pure hydrogen fueling on fuel consumption and NOx emissions in a small DI SI engine

In the last few years, car manufacturers are moving toward electrified powertrains, like Battery Electric Vehicles (BEV) and Hybrid Electric Vehicles (HEV), to reduce the levels of CO2 in the atmosphere. A promising alternative to BEVs to reduce CO2 emissions, while maintaining an existing and well-developed technology, could be the use of hydrogen for internal combustion engines (ICEs). Particularly, the zero-carbon content of hydrogen allows for guaranteeing very clean combustion and near-zero carbon footprint. Within this context, the present study aims to deeply investigate the effects of pure hydrogen fueling of Spark Ignition (SI) engines, especially on specific fuel consumption and NOx emissions. Particularly, the benefits of pure hydrogen fueling were assessed in a production small Direct Injection (DI) SI engine. The engine is intended to operate in steady state conditions as an Auxiliary Power Unit (APU) for a series hybrid powertrain. The effects of pure hydrogen fueling were investigated at two engine speeds, namely 2000 and 3000 rpm. All tests were carried out at unthrottled conditions and lean mixture. A 1-D engine model was developed within a commercial software. Combustion, heat transfer, and NOx emissions embedded sub-models were tuned based on the experimental data, to accurately reproduce the engine behavior in a wide range of operating conditions. Both experimental and simulation results demonstrated that hydrogen fueling, together with lean mixture operation, allow for significantly improving engine thermal efficiency. The results of 1-D model simulations supported the energy management strategies of the hybrid powertrain in selecting the most suitable ICE operating condition. Particularly, the best engine operating conditions in terms of fuel consumption are achieved at 2500 rpm, with λ = 2.0, while the lowest NOx emissions are reached when λ is increased up to 2.4.

TD3-Based EMS Using Action Mask and Considering Battery Aging for Hybrid Electric Dump Trucks

The hybrid electric dump truck is equipped with multiple power sources, and each powertrain component is controlled by an energy management strategy (EMS) to split the demanded power. This study proposes an EMS based on deep reinforcement learning (DRL) algorithm to extend the battery life and reduced total usage cost for the vehicle, namely the twin delayed deep deterministic policy gradient (TD3) based EMS. Firstly, the vehicle model is constructed and the optimization objective function, including battery aging cost and fuel consumption cost, is designed. Secondly, the TD3-based EMS is used for continuous action control of ICE power based on vehicle state, and the action mask is applied to filter out invalid actions. Thirdly, the simulations of the EMSs are trained under the CHTC-D driving cycle and C-WTVC driving cycle. The results show that the action mask improves the convergence efficiency of the strategies, and the proposed TD3-based EMS outperforms the deep deterministic policy gradient (DDPG) based EMS. Meanwhile, the battery life is extended by 36.17% under CHTC-D and 35.49% under C-WTVC, and the total usage cost is reduced by 4.30% and 2.49% when the EMS considers battery aging. In summary, the proposed TD3-based EMS can extend the battery life and reduce usage cost, and provides a method to solve the optimization problem for the EMS of hybrid power systems.

Стратегические ориентиры экономико-правовых механизмов декарбонизации хозяйственной деятельности в России

This paper describes the economic and legal mechanisms of decarbonization in Russia, e.g., stimulating the transition to renewable energy, the state strategy on hydrogen, green transport, etc. In Russia, decarbonization will increase in relevance following the target scenario of climate regulation. Carbon taxes are being introduced to link manufactured products to carbon footprint. Car companies plan the number of internal combustion engines to be produced based on their carbon footprint allowances. When approaching a critical point, they have to produce electric cars or hybrid engines to increase possible sales. International financial organizations make decisions on loans based on the way a country meets its climate obligations.

Battery Technology – A Comprehensive Review

Depletion of fossil fuels, stringent pollution norms have made a way for research on the systems that can store energy from renewable sources like solar and wind. Electrical vehicles (EVs) and hybrid vehicles (HEVs) density worldwide are increasing at faster rate and have projection estimate of more than 140 million (HEVs) and EVs on the road by 2030. Design of these advanced engines are based on the availability power source namely lithium-ion (Li-ion) battery. This paper focuses on available battery technologies, components of Li-ion batteries, key features of the battery such as energy density, power density and so on and opportunities of recycling, extraction of valuable metals from the waste batteries are also included.