Series Hybrid Vehicle Research Articles

New vehicle control strategy for fuel consumption and battery state of health improvement in a series hybrid vehicle utilizing fuzzy logic

New vehicle control strategy for fuel consumption and battery state of health improvement in a series hybrid vehicle utilizing fuzzy logic

Evaluation of the efficiency of a hybrid ICE vehicle fuelled with hydrogen compared with a fuel cell vehicle, based on a simulation model

With the renewed interested in the application of hydrogen on transportation, promoted also by the EU policies, the natural technology to adopt such energy vector is the fuel cell. The aim of this paper is to compare the performances, in terms of efficiency, hybrid internal combustion engine vehicles fuelled with hydrogen and fuel cell vehicles. The potential advantages, in using the ICEs, in a parallel hybrid powertrain, even if its efficiency is lower than fuel cell one, are the more efficient transmission efficiency, due to the fact that the engine is directly connected to the wheel through a gearbox, that has traditionally a very high efficiency, while the storage system help the engine when its efficiency is very low, recovering also energy during regenerative brakes. A fuel cell vehicle is generally a series hybrid vehicle, where the fuel cell has a higher efficiency than ICE, but the energy conversion from fuel cell to the electric motor has a lower efficiency. The expected result of this comparison is that the ICE hydrogen fuelled is able to recover the great part of the efficiency Gap with a higher powertrain efficiency. The study has been made using an in-house simulation code written in ENEA, using as input data the characteristic of two different vehicles, with, their electric subsystems (battery storage, electric motors, converters etc) control strategies running fixed driving cycles (e.g. the WLTC driving cycle) and comparing the fuel consumption end the efficiency.

Examining Real-Road Fuel Consumption Performance of Hydrogen-Fueled Series Hybrid Vehicles

The use of hydrogen fuel produced from renewable energy sources is an effective way to reduce well-to-wheel CO2 emissions from automobiles. In this study, the performance of a hydrogen-powered series hybrid vehicle was compared with that of other powertrains, such as gasoline-powered hybrid, fuel cell, and electric vehicles, in a simulation that could estimate CO2 emissions under real-world driving conditions. The average fuel consumption of the hydrogen-powered series hybrid vehicle exceeded that of the gasoline-powered series hybrid vehicle under all conditions and was better than that of the fuel cell vehicle under urban and winding conditions with frequent acceleration and deceleration. The driving range was longer than that of the battery-powered vehicle but approximately 60% of that of the gasoline-powered series hybrid. Regarding the life-cycle assessment of CO2 emissions, fuel cell and electric vehicles emitted more CO2 during the manufacturing process. Regarding fuel production, CO2 emissions from hydrogen and electric vehicles depend on the energy source. However, in the future, this problem can be solved by using carbon-free energy sources for fuel production. Therefore, hydrogen-powered series hybrid vehicles show a high potential to be environmentally friendly alternative fuel vehicles.

Power Generation Control Method of Fixed-power Parallel Resonant PMSG System for Series Hybrid Vehicle

Power Generation Control Method of Fixed-power Parallel Resonant PMSG System for Series Hybrid Vehicle

Co-Optimization of Design and Control of Energy Efficient Hybrid Electric Vehicles Using Coordination Schemes

AbstractDesign and control co-optimization studies for hybrid vehicles have been proposed in the past. However, such works suffer from difficulties arising due to (a) diverse real- and integer-valued variables, (b) complex nonlinear powertrain dynamics and design interconnections, (c) conflicting objective functions with path constraints, and (d) high computational resources requirements. To meet these challenges, this study presents an efficient co-optimization framework for hybrid electric vehicles (HEVs) which is built using existing algorithms and coordination schemes. Particular emphasis is given to the simultaneous scheme and the decomposition-based scheme. The decomposition-based scheme with the problem decomposition proposed in this work can efficiently handle multitime scale state variables and both integer- and real-valued design and control optimization variables. This is demonstrated by solving the mixed-integer optimal design and control problem of a series hybrid vehicle over a 1-h long drive cycle with time discretization of 1 s. The problem complexity is elevated by using an increasing number of state variables (including battery state of charge, battery energy, and after-treatment system temperature), control variables (such as the engine power and engine on/off), and design parameters (such as the number of battery cells and the type and size of the engine). In addition, a multi-objective cost function is used to find a tradeoff solution between fuel consumption and emissions minimization. The results show that in terms of optimality of the solution, the decomposition-based scheme is comparable with the simultaneous but can give a 14% improvement in computational performance. The effectiveness of the proposed framework is demonstrated by comparing the co-optimization results against a baseline case in which only the optimal control problem is solved. The co-optimized solution yields up to 3.7% average genset efficiency improvement and a fuel consumption reduction to 1.6 kg from 2.5 kg, which is further reduced to 1.5 kg by adding the engine on-off control. Finally, a decision matrix is developed to provide guidance on the selection of the optimization algorithm and coordination scheme for any problem at hand.

Aplikačné možnosti HCCI technológie

This text describes the current state of the art of HCCI technology, which is based on combining the characteristics of a petrol and diesel engine. HCCI engines offer higher fuel efficiency and lower nitrogen oxide emissions. However, they also have disadvantages such as limited load range, control complexity and cold weather starting problems. The next section of the text discusses hybrid propulsion, which uses a combination of an internal combustion engine and an electric motor. It describes the different types of hybrid powertrains such as soft hybrids, plug-in hybrids and full hybrids. Explains their advantages and possible applications. A solution is then proposed where the HCCI engine would serve as a generator in a series hybrid vehicle with an electric motor. Such an arrangement allows optimization of energy use and reduction of emissions. Finally, the relevance of HCCI technology for improving the efficiency of fuel engines and hybrid vehicle design is evaluated.

An Energy Management Strategy of Power-Split Hybrid Electric Vehicles Using Reinforcement Learning

With the rapid development of science and technology, the automobile industry is also gradually expanding due to which energy security and ecological security are seriously threatened. This paper was aimed at studying the energy organization strategy of power-split hybrid electric vehicles based on a reinforcement learning algorithm. A power-split hybrid electric vehicle (HEV) combines the advantages of both series and parallel hybrid vehicle architectures by using a planetary gear set to split and combine the power generated by electric machines and a combustion engine. This improves the fuel economy to some extent. However, to increase the fuel economy to a greater extent. This study primarily introduces the hybrid electric vehicle’s structure and presents a reinforcement learning-based management of energy approach for hybrid electric vehicles. It constructs the vehicle power model of HEV and Markov probability transfer model, then designs the energy control strategy based on reinforcement learning, and finally compares it with the energy control strategy based on PID (Proportional-Integral-Derivative). Using MATLAB/Simulink, the cycle conditions of NEDC (New European Driving Cycle) and FTP-75 (Federal Test Procedure) are selected to carry out simulation experiments. The energy management technique suggested in this study, which is based on reinforcement learning, may efficiently enhance the usage rate of automotive gasoline. The replication results show that the fuel consumption per 100 km (kilometers) based on reinforcement learning management strategy is 4.6% and 2.7% lower than the PID management strategy under two working conditions. The economy of fuel of the hybrid electric vehicle is also effectively improved.

Impact of low carbon fuels (LCF) on the fuel efficiency and NOx emissions of a light-duty series hybrid commercial delivery vehicle

This work evaluates the potential of using four different low carbon fuels (LCF) in a series hybrid vehicle concept and compares the results to a conventional diesel combustion counterpart. To do this experimental data from a low NOx emission calibration is obtained for each of the different fuels, and 0-D vehicle simulations of an OPEL Movano van model are made to evaluate the performance, in terms of fuel consumption and engine-out NOx, during the Worldwide harmonized Light vehicles Test Cycles (WLTC) using a simplified engine map strategy. The vehicle selection allows to evaluate the scenario of a delivery application with three different payloads 0%, 50% and 100%. The work is motivated by the current automotive industry’s need to reduce emissions and use energy resources efficiently, evaluating different strategies to fulfil both objectives. The evaluation of different energy sources –such as LCF– and powertrains, have been extensively researched topics, however the information is more scarce using a combination of both strategies. The results from this work show that series hybrid vehicle presents a reduction of fuel consumption of up to 5% with 100% payload, across all fuels tested. Nonetheless, engine-out emission levels of NOx show 16% worse performance for the hybrid case due to its operation at higher engine speeds and loads during the charging of the battery.

Optimal Power Control for a Variable-Speed Generator Integrated in Series Hybrid Vehicle

In series hybrid electric vehicles, the fossil energy source is composed of an electrical generator driven by an internal combustion engine. Compared to constant speed control, variable speed control of the electrical generator improves the vehicle’s energetic efficiency and releases the battery load. Such control is extremely sensitive because of the nonlinearities. In a plug-in hybrid vehicle, in addition to the obvious inherent variable speed nonlinearity, the large range of battery voltage variation increases the complexity of the controller design. Moreover, in our case, to take advantage of the variable speed feature, the generator load has transient constraints because it must follow the vehicle load. In equivalent applications, for the electrical side, usually, there is a use of high-frequency control strategies based on the generator’s three phases current and voltage acquirement. This article investigates a low-frequency power control strategy through a model-based method for a specific power electronics vehicle architecture. Starting with an adaptive proportional, integrator, and derivative (PID)-based controller to tackle the nonlinearity issues, this article explains progressively the reasons and choices that lead to design a sliding hybrid fuzzy logic controller. The designed controller demonstrates good performance in power tracking and permits to reduce fuel consumption.

Comparative analysis of state of charge based adaptive supervisory control strategies of plug-in Hybrid Electric Vehicles

In this era of vehicle electrification from mild hybrids to fully electric cars, the importance of fuel economy improvements has led to technological advancements in energy management strategies. The control algorithm is pivotal to the increase in the energy efficiency of a plug-in hybrid system. The existing energy management strategies lack the adaptiveness and utilization of advancements of vehicle-to-vehicle technology. This paper proposes a Cost Optimization for Finite Horizon strategy and also an adaptive version of Equivalent Consumption Minimization Strategy (A-ECMS). The Adaptive-ECMS adds a battery State of Charge (SOC) based reference to ensure the most efficient blended operation for a charge-discharge cycle. The Cost Optimization for Finite Horizon strategy utilizes future driving condition information from vehicle-to-vehicle technology to assist fuel consumption. A forward-looking vehicle propulsion system simulator is developed in Simulink®. A battery model is developed with parameters from the Nickel Cobalt Aluminum chemistry cell. To understand the extent of improvement, the proposed strategies are then compared with the prevalent Finite State Machine strategy (FSM) in three representative driving cycles. The results show an average fuel economy improvement of 5% when compared to the baseline strategy. Among the three strategies, Cost Optimization for Finite Horizon strategy is best suitable for urban driving conditions and Adaptive-ECMS is best suitable for highway driving conditions. For a conventional series-hybrid vehicle, implementing the proposed energy management strategies can help save approximately 8.5 gallons of fuel per year.

A simulation and experimental study of an innovative MAC/ORC/ERC system: ReverCycle with an ejector for series hybrid vehicles

This paper presents the simulations and experiments for the development of a hybrid and reversible mobile air conditioning, organic Rankine cycle (ORC), and ejector refrigeration cycle (ERC) system. This flexible and compact system may be the solution to the introduction of waste heat recovery in passenger cars. The cycle fuel economy is calculated for series hybrid electric vehicles (SHEVs). A global vehicle model is used to simulate the annual weather conditions of different climatic regions. The reference driving cycle is the Worldwide Harmonized Light Vehicle Test Cycle.The cycle fuel economy is maximized in temperate and cold climatic regions. In the hypothesized engine cold-start initial condition, the SHEV ReverCycle maximum fuel economy is 1.2% in Paris. In the hot-start initial condition, the SHEV ReverCycle maximum fuel economy is 2.2% in Moscow. The experimental results of the ReverCycle proof of concept are then presented. The maximum measured net efficiency in the ORC mode is 3.9%. The ERC mode can satisfy cabin cooling requirements at an ambient temperature below 20 °C. The estimated fuel economy in the ERC mode is 1.4%.

DC Power Generation Systems with Permanent Magnet Synchronous Machines and Full-Bridge Rectifiers Using Resonant Circuits

Series hybrid vehicles use power generation systems with engine-powered generators and rectifiers. Systems with permanent magnet synchronous machines and full-wave rectifiers are expected to be efficient and inexpensive. However, it is difficult to increase the output power density of the generator because the generated voltage cannot be increased beyond the induced voltage by permanent magnets. This paper describes the process of improving the power density of a system by adding capacitors to the system to form a resonant circuit.

Characterisation of micro turbine generator as a range extender using an automotive drive cycle for series hybrid electric vehicle application

This study investigated a micro turbine generator (MTG) as a range extender for a series hybrid electric vehicle application for a range of constant and dynamic power demand strategies. The power demands were calculated through a mathematical model based on a specific vehicle platform using the New European Drive Cycle (NEDC). The power demands were then used to characterize the MTG in a controlled test environment. Each of the strategies produced interesting results in terms of fuel consumption, specific emissions, net efficiency, and power responses. The experimental results revealed the lowest specific emissions, and fuel consumption while the MTG operated at constant power demand. One of the dynamic power demand strategies also produced low fuel consumption, but with higher specific emissions. Although exhaust emissions in each strategy were well below the Euro 6c limits. These results indicate the potential of MTG as a range extender in a series hybrid vehicle. Even, the MTG can be operated dynamically with relatively low fuel consumption and very low specific emissions, compared to the traditional approach of a constant power demand.

Resonant Combustion Start Considering Potential Energy of Free-Piston Engine Generator

Free-piston engine generators without a crank mechanism are expected to be used in series hybrid vehicles because of their lower losses. The series hybrid system requires a low starting thrust because the engine frequently starts depending on the battery state. This study clarifies the effectiveness of the constant thrust resonance starting method that utilizes the compression pressure of the engine and the spring thrust. The piston must pass the combustion starting point with a predetermined speed to start combustion. Herein, we present a thrust setting method that uses the energy state diagram to optimize the velocity at the combustion start point. A simulation is performed assuming output when mounted on a vehicle. Consequently, the simulation results show that the maximum thrust can be reduced by more than 90% compared to that without resonance. Moreover, the speed at the combustion start point is in agreement with the value obtained using an energy state diagram. An impulse-like combustion pressure is generated in 180 ms, and combustion can be started using resonance, as shown in an experiment using a small-output engine and linear motor. The effectiveness of the constant thrust resonance starting method was confirmed.

Turbocompound Power Unit Modelling for a Supercapacitor-Based Series Hybrid Vehicle Application

In this paper, starting from the measurements available for a 2000 cm3 turbocharged diesel engine, an analytical model of the turbocharger is proposed and validated. The model is then used to extrapolate the efficiency of a power unit with a diesel engine combined with a turbocompound system. The obtained efficiency map is used to evaluate the fuel economy of a supercapacitor-based series hybrid vehicle equipped with the turbocompound power unit. The turbocompound model, in accordance with the studies available in the technical literature, shows that the advantages (in terms of efficiency increase) are significant at high loads. For this reason, turbocompound introduction allows a significant efficiency improvement in a series hybrid vehicle, where the engine always works at high-load. The fuel economy of the proposed vehicle is compared with other hybrid and conventional vehicle configurations.

High power density by combining of a double stator and an opposite-magnets linear generator in a dual-type free-piston engine generator

A linear generator system based on a free-piston engine is expected to be a highly efficient power-generation engine for series hybrid vehicles. However, the engine generator must produce in a limited installation space the very high power required to drive a car. Consequently, considering the car-mounting situation, higher power density is required by means of reduced generator size and higher efficiency. In this paper, a cylindrical double-stator linear synchronous generator with opposing permanent magnets is used for free-piston engine. The double stator realizes smaller size, and using opposing magnets achieves a larger thrust constant than that with a single stator. In a finite-element analysis, the high-efficiency area is expanded compared to a surface-magnet type of the same size. Furthermore, this paper clarifies the effectiveness for improved power density with maximum-generation control in a simulation of a dual-sided engine model.

Design and Development of Series-Hybrid Automotive Powertrains

The new global pandemic determines people to change their ordinary habits, so personal transportation will play a very important role for a long period of time from now on. However, even though conventional vehicles offer enough range for replacing some trips that normally would be covered by planes, they have a harmful impact on the environment. By comparison, Electric Vehicles (EVs) suffer from this shortcoming (insufficient range), being more expensive, as well. Therefore, this article presents a very simple, unique and inexpensive methodology for designing the powertrain of a plug-in series-hybrid vehicle, based on measurements (regarding the engine torque requirements, but not limited to) performed on a compact passenger car, during real driving conditions, as well as based on mathematical calculations and computer-aided simulations (using MATLAB Simulink). The parameters of the proposed series-hybrid driving system which have been determined refer to the specifications of the Internal Combustion Engine (ICE) which is used to drive a generator, the rated output power of the electric generator, the required capabilities of the electric motor which is used to drive the wheels, the capacity of the high voltage battery pack (which supplies the electric motor), together with its other attributes, taking into consideration the vehicle’s overall performance and characteristics. Besides this, it has been developed a very simple algorithm that manages the power generated by the engine and which can reduce the fossil fuel consumption with almost 38%, on average, compared to a conventional drivetrain.

Fuel Economy and EMS for a Series Hybrid Vehicle Based on Supercapacitor Storage

The large-scale spread of hybrid electric vehicles (HEVs) in the automotive industry is dominated today by continuous variable transmission parallel powertrain as far as medium size car are concerned. As a matter of fact, the tendency in this sector is to design parallel architectures in that they have provided until now a higher overall powertrain efficiency. However, technological improvements in many electric components and their increased efficiency can reshape this vision and give new outlines on HEV structure design. This paper aims to show the potentials of the series architecture, thanks to the latest electrical improvements especially in storage systems and power electronics. In particular, simulation models and fuel consumption data over different road missions are presented for the series architecture proposed in this study. In addition, a comparison between these results and data available in the scientific literature for state-of-the-art HEVs is reported.

Improving the constant‐volume degree of combustion considering generatable range at low speed in a free‐piston engine linear generator system

Series hybrid vehicles using free‐piston engine coupled with linear generator are expected for high‐efficiency energy conversion systems. Such engines do not have a crank mechanism, which greatly reduces the friction loss. In addition, the piston action can be controlled freely by the generation braking thrust by using an inverter control. In a conventional crank engine, past research has shown that delaying the piston motion after the combustion increases the maximum combustion pressure, and this delay brings a constant‐volume degree close to the Otto cycle. In the free‐piston system, a high braking thrust is needed at a low piston speed immediately after combustion. However, the highest braking thrust was limited in the low‐speed range because the back electromotive force of a permanent magnet synchronous generator was too small. This article shows the range that can be theoretically attained for a low‐speed generator. The delaying piston movement with only the braking thrust improved the effective work by 25% near the top dead center. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Enhancing the fuel economy of a plug-in series hybrid vehicle system

Abstract In this paper, the design and simulation of a hybrid vehicle with a fully functional driving model is presented. Actual velocities and desired velocities are compared and matched to get the optimum values of a vehicle. Fuel economy is calculated to get miles per gallon gasoline equivalent (MPGe). The MPGe for a hybrid vehicle is compared with the MPGe for a conventional vehicle to get the best MPGe in a hybrid car. A higher performance of output power of a vehicle is obtained.