Performance Of Hybrid Vehicle Research Articles

Study on the Selection of Electric Motor/Engine on the Performance of Hybrid Vehicles

Study on the Selection of Electric Motor/Engine on the Performance of Hybrid Vehicles

Impact of Engine Inertia on P2 Mild HEV Fuel Consumption

The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion engine (ICE). It is therefore one of the main factors that can significantly influence the fuel consumption and performance of hybrid vehicles. In the transmission path, the power generated by the ICE is in part employed to accelerate the rotating components of the powertrain, such as the crankshaft, flywheel, gears, and shafts. The main inertial components are the crankshaft and the flywheel. This additional power is significant during high-intensity acceleration. Therefore, the actual engine operation is different from that required by the power split unit. This study focuses on exploring the influence of engine inertia on HEV fuel consumption by developing a controller based on an equivalent consumption minimisation strategy (ECMS) that considers crankshaft and flywheel inertia. The optimal solution obtained by the ECMS controller is refined by incorporating the inertia effect of the main rotating components of the engine into the cost function. This reduces the engine operation during high inertial torque transient phases, resulting in a decrease in vehicle CO2 emissions by 2.34, 2.22, and 1.13 g/km for the UDDS, US06, and WLTC driving cycles, respectively.

Research on energy redistribution of hybrid vehicle considering thermal constraints

Thermal management is one of the key factors affecting the performance of hybrid vehicles. However, most traditional energy management strategies lack the consideration of thermal constraints under harsh operating conditions. In this paper, taking a specific type of diesel-electric hybrid system as the research object, a strategy for energy redistribution under thermal management constraints is proposed. The diesel-electric hybrid system model is built and verified. Based on the model, the cooling capacity indexes are selected, and the weight coefficient of each cooling capacity index is determined by neighborhood component analysis. Then a comprehensive thermal evaluation system is obtained. Combined with the thermal evaluation system, the energy redistribution strategy based on the momentum gradient descent method is proposed. Two typical working conditions of high altitude and battery cooling system deterioration are selected, and the energy redistribution strategy is simulated and analyzed in real-time under both working conditions. The results show that the energy redistribution strategy can significantly improve the thermal state of the system at the expense of less overall energy consumption, take into account the economy and thermal balance, and ensure the reliable operation of the vehicle.

Internal Combustion Engine Starting and Torque Boosting Control System Design with Vibration Active Damping Features for a P0 Mild Hybrid Vehicle Configuration

In order to meet the increasingly stricter emissions’ regulations, road vehicles require additional technologies aimed at the reduction of emissions from the internal combustion engine (ICE). A favorable solution from the standpoint of costs and simplicity of integration is a 48-V electrical architecture utilizing a low-voltage/high-power induction machine, which operates as the so-called engine belt starter generator (BSG) coupled via a timing belt with the ICE crankshaft within a P0 mild hybrid power train and used for starting up and boosting of the ICE power output, as well as for recuperating kinetic energy during vehicle deceleration. The aim of this work was to design a vibration damping system for the belt transmission within the so-called front end accessory drive (FEAD), which couples the BSG with the ICE crankshaft and to test the control system by means of simulations for realistic operating regimes of the P0 mild hybrid power train in order to show the functionality of the proposed approach in terms of mild hybrid vehicle performance improvement. Simulation results have pointed out effective attenuation of belt compliance-related vibrations using the proposed active damping control, with vibration magnitude reduced between three and five times compared to the default case during engine start-up phase. They have indicated the realistic belt slippage effects during engine start-up phase and have illustrated the effectiveness of the FEAD torque boosting capability with 30% gain in acceleration during vehicle launch.

Research on regenerative braking strategies for hybrid electric vehicle by co-simulation model

Regenerative braking is an important factor in improving hybrid electric vehicle (HEV) fuel economy. This paper presents the simulation modelling of a power-split hybrid electric vehicle with different regenerative braking strategies. A co-simulation model is used to enhance the simulation capability for the hybrid vehicle performance and development of control strategy. AMESim is used to model the complex physical components including engine, transmission, motors, battery and hybrid vehicle, and the physical model is integrated with control model established by MATLAB/Simulink, which is required to operate the vehicle and the regenerative braking system through standard drive cycles. Simulation results show that a regenerative braking control strategy can recuperate significant amounts of energy. Vehicle fuel economy in EV and HEV modes is improved significantly by coupling the proposed regenerative braking strategy.

Shift scheduling strategy development for parallel hybrid construction vehicles

The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construction vehicles. The effect of power distribution and direction on shift characteristics of the parallel hybrid vehicle with operating loads is evaluated, which must be considered for optimal shift control. A power distribution factor is defined to accurately describe the power distribution and direction in various parallel hybrid systems. This paper proposes a Levenberg-Marquardt algorithm optimized neural network shift scheduling strategy. The methodology contains two objective functions, it is a dynamic combination of a dynamic shift schedule for optimal vehicle acceleration, and an energy-efficient shift schedule for optimal powertrain efficiency. The study is performed on a test bench under typical operating conditions of a wheel loader. The experimental results show that the proposed strategies offer effective and competitive shift performance.

Investigation of the effects of battery types and power management algorithms on drive cycle simulation for a range-extended electric vehicle powertrain

ABSTRACTFuel cell (FC) hybrid vehicle power trains are an attractive technology especially for automotive applications because of their higher efficiency and lower emissions compared to conventional vehicles. This study focuses on the design of an FC hybrid power train system and evaluation of its simulations for a given speed profile through two alternative power management algorithms (PMAs). Parameters suitable for a small vehicle were taken into consideration in the mathematical model of the vehicle. The proposed hybrid power train consists of an energy storage system, composed of a 4-kg battery pack (either lithium-ion (Li-ion) battery, nickel metal hydride, or nickel–cadmium) and a direct methanol fuel cell (DMFC) as the range extender. The PMAs basically aim to fulfill the power requirements of the vehicle and decide how to command the power split between the battery and the FC. The model comprising a DMFC, a battery, and PMAs was developed in MATLAB/Simulink environment. The polarization curve of the FC was obtained using a one-dimensional DMFC model. Vehicle power requirements for a drive cycle were calculated using the equations of longitudinal dynamics of vehicle, and the results were integrated into MATLAB/Simulink model. As a result of the simulations, methanol consumption, state of charge of the battery, and power output of the FC were compared for the PMAs. This comparison shows the effect of PMAs on the hybrid vehicle performance for three battery types. The results indicate that the vehicle range could be increased when proper strategy is used as PMA.

Influence of a CVT on the fuel consumption of a parallel medium-duty electric hybrid truck

Hybrid electric vehicles are being developed to reduce the pollutant emissions and the fossil-fuel consumption of transportation. Innovative technologies are inserted to improve the performance of hybrid vehicles, including trucks and buses. Thereby, trends towards gear shifting automation motivate the research on replacing a discrete conventional Automated Manual Transmission (AMT) with a Continuously Variable Transmission (CVT). Theoretically, such a transmission enables better operation points of the thermal engine, and therefore a reduction of its fuel consumption and emissions. However, the conventional (hydraulic actuated) CVT efficiency during quasi-stationary operation is typically lower than the efficiency of a classical discrete gearbox, which leads to higher fuel consumption. This paper is focused on the study of the interests of a CVT for a medium-duty Hybrid Electric Truck (HET). The complete model and control of CVT-based and AMT-based HET are described in a unified way using Energetic Macroscopic Representation (EMR). These models are transformed to backward-models to be computed by the Dynamic Programming Method (DPM). Such a method leads to define the (off-line) optimal energy management strategies for a fair comparison of both hybrid trucks. For the studied driving cycle, the hybridization allows a fuel saving of 10% with an AMT and 3% with a CVT. The fuel consumption is higher for the CVT-based HET in comparison with the AMT-based HET due to the lowest efficiency of the CVT (85%) compared to the AMT (around 92%). However, future (on-demand) CVTs with an increased efficiency could be a solution of interest to reduce the fuel consumption of such applications. The developed method can be used to test these new CVTs, other vehicles or other driving cycles.

Synthesis of Predictive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles Based on Closed-Form Solution of Optimal Equivalence Factor

Previously, an equivalent consumption minimization strategy (ECMS) was developed that provides near-optimal performance of hybrid vehicles based on an adaptation of equivalence factor from state of charge feedback. However, under real-world driving conditions with uncertainties, such as hilly roads, ECMS requires a predictive scheme utilizing future driving information in order to prevent a loss of optimality. In this paper, we synthesize predictive ECMS in a feedforward way to adjust the equivalence factor based on its theoretical connection with future driving statistics, in a systematic manner. First, a useful noncausal adaptation strategy is extracted from dynamic programming results. Then, the inverse problem is formulated and solved to derive an explicit representation of the constant optimal equivalence factor with justified assumptions. Finally, a causal, predictive adaptation strategy using this closed-form solution is synthesized to mimic the noncausal one, and its effectiveness is evaluated for fuel cell hybrid electric vehicles. Results show that if the predicted statistical information reflects well the future driving conditions, the proposed strategy accurately estimates the constant optimal equivalence factor, including the jump behavior, thereby yielding less than 1.5% loss of fuel optimality. Moreover, this approach is extendible to other configurations.

Reducing the Fuel Consumption and Pollution by Designing the Optimal Energy Management in Hybrid Vehicles

Objective: One of the main factors in fuel consumption and pollution is transportation and automotive industry. Today one of the most effective methods to deal with pollution and fuel consumption is developing the hybrid electric. Method: This type of propulsion system has been used of two combined power sources of the internal and electric combustion engine alongside each other for providing the required power to drive the vehicle and in addition to that, they remove each other's limitations by using the overlapping simultaneously. Results: One of the main important parameters in optimal hybrid vehicles performance is the energy management system appropriate designing between the power sources that it is the main factor in optimal performance of hybrid vehicles. Therefore, in this research, first the hybrid vehicle modeling is presented, including the combustion engine, gearbox, electric motor and battery with the association of Advisor-Simulink. Then, the optimal energy management system is designed for the optimal distribution of power between the combustion and electric engine according to the fuzzy logic. Findings: It shows that it can be reduced the fuel consumption and pollution by using the electric auxiliary power source along with combustion engine and optimal energy management in different conditions. Applications/Improvements: Finally, the sensitivity analysis of the effect of weight on vehicle performance will be assessed.

An Investigation of Fuel Economy Potential of Hybrid Vehicles under Real-World Driving Conditions in Bangkok

This study attempted to investigate fuel economy performance of hybrid vehicles under real-world driving conditions in Bangkok. The effect of traffic conditions and driving styles were taken into account. To cover the variations in traffic conditions, city, suburban and highway traffic were selected to represent the variety of traffic flow. For the effect of driving styles, the experiment was conducted by four experienced drivers, two aggressive and two normal-calm drivers. Statistical parameters, average speed and acceleration noise, were employed to quantify and analyse the impact of Bangkok traffic conditions and driving styles on both vehicles’ fuel consumption. This study integrated microtrip segmentation technique into the data analysis. Experimental results illustrated that HVs were capable of reducing fuel consumption of CVs in all traffic conditions and driving styles covered by this study. Particularly in the congested traffic in Bangkok, HVs potentially decreased the fuel consumption by a maximum of 47.3%. More importantly, HVs greatly mitigated the effect of aggressiveness on excessive fuel consumption in practical driving habits, although they appeared to be more sensitive to aggressiveness than CVs.

Optimal Rule-Based Power Management for Online, Real-Time Applications in HEVs with Multiple Sources and Objectives: A Review

The field of hybrid vehicles has undergone intensive research and development, primarily due to the increasing concern of depleting resources and increasing pollution. In order to investigate further options to optimize the performance of hybrid vehicles with regards to different criteria, such as fuel economy, battery aging, etc., a detailed state-of-the-art review is presented in this contribution. Different power management and optimization techniques are discussed focusing on rule-based power management and multi-objective optimization techniques. The extent of rule-based power management and optimization in solving battery aging issues is investigated along with an implementation in real-time driving scenarios where no pre-defined drive cycle is followed. The goal of this paper is to illustrate the significance and applications of rule-based power management optimization based on previous contributions.

Development a new power management strategy for power split hybrid electric vehicles

Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In order to simulate the hybrid vehicle, the combined feedback–feedforward architecture of the power-split hybrid electric vehicle based on Toyota Prius configuration is modeled, together with necessary dynamic features of subsystem or components in ADVISOR. Multi input fuzzy logic controller developed for energy management controller to improve the fuel economy of a power-split hybrid electric vehicle with contrast to conventional Toyota Prius Hybrid rule-based controller. Then, effects of battery’s initial state of charge, driving cycles and road grade investigated on hybrid vehicle performance to evaluate fuel consumption and pollution emissions. The simulation results represent the effectiveness and applicability of the proposed control strategy. Also, results indicate that proposed controller is reduced fuel consumption in real and modal driving cycles about 21% and 6% respectively.

Investigation of the energy management and powertrain systems effects on hybrid vehicle performance

Reduction of greenhouse gas emission and fuel consumption is one of the main goals of automotive industry leading to the development of hybrid vehicles. Energy management, energy storage and transmission systems are the significant factors that affect hybrid vehicle performance. In this paper different powertrain system component combinations effects are investigated on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. Results are compared in different traffic conditions, such as a newly established Teh-car, NEDC and FTP driving cycles. Hybrid vehicle simulation results are compared for various transmission and energy storage systems by using ADVISOR. Results indicate the effectiveness of proposed controller over real world driving cycles. Also, the optimal powertrain configuration which improves fuel and emissions efficiency is proposed for each driving condition. Finally, the effects of batteries' initial state of charge are investigated on hybrid vehicle performance to evaluate fuel consumption and emissions.

Modeling, performance simulation and controller design for a hybrid fuel cell electric vehicle

In this paper, a PEM fuel cell hybrid vehicle performance is studied. Main components of this hybrid vehicle are: fuel cell power system, DC–DC converter, battery, electric motor and transmission system. The fuel cell power system which is comprised of fuel cell stack and auxiliary components are modeled and simulated in a previous paper by the authors. The fuel cell is controlled so that it operates at its peak net power. Depending on driving condition, the stack temperature changes during the vehicle performance. To prevent the temperature from exceeding a limit, which is 80 °C, a PID controller is employed. The results of the power system modeling are validated using a previous study on a polymer electrolyte membrane fuel cell power system in K.N. Toosi University of Technology. The hybrid configuration of the vehicle improves its performance in acceleration, slope climbing, extending the driving range and fuel consumption. The battery state of charge (SOC) should always remain in a prescribed range. In this study, the battery SOC is controlled within its defined range during vehicle performance using two controllers. Finally, fuel consumption and vehicle performance are investigated during two driving cycles.

하이브리드 차량용 클러치 자동화 기구의 특성 연구

Due to the increase of oil price, the needs of the reduction of the fuel cost is rising. Therefore, necessity of hybrid vehicle that runs with engine and the electric motor is on the rise. In order to improve the performance of hybrid vehicle, many researches is carried out. Hybrid vehicles have been developed with the various layout such as serial type, parallel type, power split type, and multi-mode type. The multi-mode hybrid vehicles are designed to show the efficient driving characteristics at low speed and high speed. But the multi-mode system have the problem such as frequent clutch engagement. Frequent clutch engagement causes the shock of vehicles, and the shock inhibits the ride comfort. In this study, automation mechanism of clutch operation is proposed to mitigate the shock at engaging clutch. For this purpose, the dynamic characteristics of motor control is numerically analyzed by using Matlab/Simulink.

Optimal Selection of an Electric Drive System for a Series Hybrid Vehicle Using Analytic Hierarchy Process

Hybrid electric vehicles (HEVs) are built using advanced technology to reduce exhaust emissions and increase fuel economy, which are the main objectives of the automotive industry today. Motors/controllers are the most fundamental components, especially in a series configuration, to produce and control the drive force for the hybrid vehicles. This paper presents a method of selecting the optimal drive motor/controller for a series hybrid vehicles, based on the requirements. This paper provides an overview of electric drive motors/controllers and analytic hierarchy process. ADVISOR is utilised to simulate the hybrid vehicle performance, employing different categories of AC motors/controllers in the powertrain. The analytic hierarchy process is then implemented with consideration given to several performance criteria for the comparable motors/controllers of the series hybrid vehicle. Results show a typical permanent magnet motor/controller has a better performance compared to induction motors/controllers.

Optimal selection of an electric drive system for a series hybrid vehicle using analytic hierarchy process

Hybrid electric vehicles (HEVs) are built using advanced technology to reduce exhaust emissions and increase fuel economy, which are the main objectives of the automotive industry today. Motors/controllers are the most fundamental components, especially in a series configuration, to produce and control the drive force for the hybrid vehicles. This paper presents a method of selecting the optimal drive motor/controller for a series hybrid vehicles, based on the requirements. This paper provides an overview of electric drive motors/controllers and analytic hierarchy process. ADVISOR is utilised to simulate the hybrid vehicle performance, employing different categories of AC motors/controllers in the powertrain. The analytic hierarchy process is then implemented with consideration given to several performance criteria for the comparable motors/controllers of the series hybrid vehicle. Results show a typical permanent magnet motor/controller has a better performance compared to induction motors/controllers.

Electrically Heated Catalysts for Hybrid Applications: Mathematical Modeling and Analysis

In view of the significant cold-start hydrocarbon emission reduction potential of the electrically heated converter (EHC) technology for conventional stoichiometric gasoline engines, there is considerable interest in better understanding of the thermal and emission performance characteristics and optimizing the design/operating aspects of an EHC system as applied to plug-in hybrid electric vehicles (PHEVs) and extended-range electric vehicles (EREVs). The application of the EHC technology to these hybrid vehicles is unique in that catalyst cooling to below reaction temperatures can occur during extended periods of electric vehicle driving (with engine off) or during intermittent engine stops/starts, and the EHC can be heated prior to engine start (preheating) for enhanced emission reduction. In this study, the design aspects and heating strategies of an EHC system have been analyzed using a transient monolith converter model which accounts for the resistive heating of an inert metal−substrate monolith placed ahead of a conventional three-way catalytic converter. The results of model calculations presented here quantify the effects of various heating strategies on the emission performance of hybrid vehicles during the first 250 s of the Federal Test Procedure (FTP) drive cycle. It is also shown that there exists an optimum electric heater volume for cases with either preheating only or a combination of pre- and postheating. For the latter case, the emission performance can be further improved by adding a smaller electric heater (downstream of the existing heater) which is capable of heating the gas rapidly and efficiently during postheating.