Evaluating the Performances of Advanced Powertrains

Volume 2 ◽  
2004 ◽  
Author(s):  
Massimo Feola ◽  
Fabrizio Martini ◽  
Stefano Ubertini
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Hybrid Vehicles ◽  
Propulsion System ◽  
Road Vehicles ◽  
Hybrid Propulsion ◽  
Hybrid Electric

Over the last few decades a tremendous effort has been made to reduce road vehicles engines contribution to air pollution and fuel consumption. Due to the more stringent limits imposed by governments, various manufactures started working in the incorporation of alternative powertrain configurations, such as pure electric vehicles (EV), hybrid electric vehicles (HEV) and fuel cell vehicles (FCV), in the automotive consumer market. In order to appreciate the advantages and disadvantages of these new vehicles over conventional vehicles a comparison must be performed in terms of efficiency and pollutant emissions. However, hybrid vehicles comprise many components with at least two different energy conversion devices (i.e. internal combustion engine and electric machine) drawing energy from at least two different energy storage devices (i.e. fuel tank and battery). In recent times, many hybrid propulsion system configurations have emerged and many others can be imagined comprising multiple reversible and irreversible energy paths. Therefore, considering that in a hybrid vehicle at least two different forms of energy (i.e. fuel chemical energy and electricity) are consumed, fuel consumption alone is no more sufficient to give a measure of the effectiveness of a hybrid propulsion system. This paper presents a first attempt to give a general mathematical form of the traction energy, the global efficiency and the specific fuel consumption of a hybrid electric vehicle that recovers as particular cases the thermal vehicle and the series hybrid electric vehicle. To evaluate the efficiency of the generic propulsion system the complete process from fuel energy and electricity to power available at the wheels is considered. The introduced concept of equivalent fuel consumption can be the basis for the comparison between road vehicles whatever the powertrain is pure thermal or hybrid. In order to get a better understanding of the mathematical analysis and its potential effectiveness some numerical simulations of hybrid vehicles virtual prototypes are performed through a suitable simulation model. The aim of the present analysis is to provide an instrument that allow a quick evaluation of the performances of hybrid electric vehicles.

Driving shaft lifetime enhancement by hybrid electrification

2018 ◽  
Vol 233 (3) ◽  
pp. 572-584
Author(s):  
Volkan Sezer
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Power Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Conventional Vehicle ◽  
Management Algorithm ◽  
Hybrid Electric

As a classical definition, the main aim of hybrid electric vehicle technology is to decrease the fuel consumption and emissions with the assistance of its power management algorithm. However, hybrid electric vehicles could also be optimized for fatigue minimization of the driving shaft to enhance its lifetime. To the best of our knowledge, there are no studies on hybrid electric vehicles regarding this concept. In this study, we model a conventional vehicle, convert it into hybrid electric vehicle in simulation environment, and optimize the power management algorithm by considering its driving shaft lifetime enhancement. The optimization is done by redesigning one of the previous equivalent cost minimization strategy studies, which includes a new state of charge sustaining approach. In this work, we reformulate the solution considering the assumptive torque–cycle life curve of the driving shaft instead of fuel consumption or emissions. Longitudinal vehicle model is prepared for simulations and the performance of the new strategy is compared with the conventional vehicle under the real driving cycle data. The results demonstrate a significant enhancement potential of 26% in driving shaft’s lifetime. Finally, we show the additional electric motor’s optimum torque tracking performance under a real driving cycle using the experimental testbed.

Multirate Integration in Hybrid Electric Vehicle Virtual Proving Grounds

1998 ◽  
Author(s):  
Dario Solis ◽  
Chris Schwarz
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Time Scales ◽  
Electric Vehicles ◽  
Time Scale ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Differential Algebraic Equations ◽  
Vehicle Systems ◽  
Hybrid Electric

Abstract In recent years technology development for the design of electric and hybrid-electric vehicle systems has reached a peak, due to ever increasing restrictions on fuel economy and reduced vehicle emissions. An international race among car manufacturers to bring production hybrid-electric vehicles to market has generated a great deal of interest in the scientific community. The design of these systems requires development of new simulation and optimization tools. In this paper, a description of a real-time numerical environment for Virtual Proving Grounds studies for hybrid-electric vehicles is presented. Within this environment, vehicle models are developed using a recursive multibody dynamics formulation that results in a set of Differential-Algebraic Equations (DAE), and vehicle subsystem models are created using Ordinary Differential Equations (ODE). Based on engineering knowledge of vehicle systems, two time scales are identified. The first time scale, referred to as slow time scale, contains generalized coordinates describing the mechanical vehicle system that includs the chassis, steering rack, and suspension assemblies. The second time scale, referred to as fast time scale, contains the hybrid-electric powertrain components and vehicle tires. Multirate techniques to integrate the combined set of DAE and ODE in two time scales are used to obtain computational gains that will allow solution of the system’s governing equations for state derivatives, and efficient numerical integration in real time.

Control Strategy of Hybrid Electric Vehicles Based on Driving Style Identification

2014 ◽  
Vol 945-949 ◽  
pp. 1587-1596
Author(s):  
Xian Zhi Tang ◽  
Shu Jun Yang ◽  
Huai Cheng Xia
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Entropy Theory ◽  
Driving Style ◽  
Identification Error ◽  
Identification Method ◽  
Hybrid Electric

The driving style comprehensive identification method based on the entropy theory is presented. The error and error proportion of each identification result are calculated. The entropy and the variation degree of the identification error of each identification method are calculated based on the definition of information entropy. According to the entropy and the variation degree of the identification error, the weight of each kind of identification method can be determined in the comprehensive identification method, and the driving style comprehensive identification algorithm is derived. The control strategy of hybrid electric vehicles based on the driving style identification is proposed. The economic control strategy and dynamic control strategy are established. Depending on the results of driving style identification, aiming at different kinds of drivers, the mode of control strategies can be adjusted, so the demands of different kinds of drivers can be satisfied. The hybrid electric vehicle simulation model and control strategy model are built, and the simulations have been done. Due to the simulation results, the drivers’ intention comprehensive identification method based on the entropy theory is proved to represent the driver’s driving style systematically and comprehensively, and the hybrid electric vehicle control strategy based on the driving style identification can make the vehicles satisfy different drivers’ demands.

Parametric Vehicular Simulator in the Evaluation of HELVIS Mini-HEV EDS Control

2011 ◽  
Author(s):  
Rafael C. B. Sampaio ◽  
Gabriel S. de Lima ◽  
Vinicius V. M. Fernandes ◽  
Andre´ C. Hernandes ◽  
Marcelo Becker
Keyword(s):  
Artificial Intelligence ◽  
Experimental Data ◽  
Real Time ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Differential System ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Hybrid Electric ◽  
The Universe

HELVIS (Hybrid Electric Vehicle In Low Scale) is a mini-HEV platform used on the research of HEVs (Hybrid Electric Vehicles), through which students of all degrees have the opportunity to be introduced to the universe that surrounds HEVs in many aspects. In this work the HELVIS-Sim is presented. HELVIS-Sim is a full dynamic & kinematic vehicular simulator for the HELVIS platform, consisting of a Simulink™ environment through which the states of a large number of variables related to the vehicle can be observed and analyzed. Specially in this paper, the focus is in the control of HELVIS EDS (Electronic Differential System), presenting classic, A.I.-based (Artificial Intelligence) and optimal robust controllers in the problem of the adjustment of the rear angular speeds. HELVIS-Sim results are then compared to experimental data obtained from the real HELVIS EDS, with the aid of a dSpace™ real time interface board.

Modeling and Simulation of a Multiple-Regime Plug-In Hybrid Electric Vehicle

2013 ◽  
Author(s):  
Rui Cheng ◽  
Jian Dong ◽  
Zuomin Dong
Keyword(s):  
Control System ◽  
Modeling And Simulation ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Hybrid Vehicles ◽  
Rule Based ◽  
Hybrid Electric ◽  
Load Leveling ◽  
And Control

In recent years, the automotive industry has devoted considerable resources to the research and development of hybrid vehicles. Plug-in hybrid electric vehicles (PHEV) present to be the next generation hybrid vehicles that offer the advantages in reducing fossil fuel consumption and lowering emissions without sacrifice vehicle performance, and the ability to utilize renewable energy through charge from the electric grid. In this work, the powertrain model of a series-parallel, multiple-regime plug-in hybrid electric vehicle (SPMR-PHEV) was introduced. As one of the several parallel powertrain modeling, simulation and control system design approaches at University of Victoria, the presented SPMR-PHEV model was developed using rule-based load-leveling energy management strategy (EMS) under the MATLAB/Simulink and SimDriveline environment. In order to validate the model and evaluate the fuel consumption and performance of SPMR-PHEV, a Simulink based Prius model and two different PHEV powertrain models have also been built using Autonomie — a vehicle simulation tool developed by DOE’s Argonne National Laboratory, using the default control logics. Fuel consumption from the three different models were compared using a test drive case consisting of eight times of the US06-City drive cycle. Under the static modeling and simulation method and different control strategies, the SPMR-PHEV model in Simulink/SimDriveline and rule-based load-leveling EMS showed 12.02% fuel economy and powertrain efficiency improvements over the Autonomie model. The new powertrain system model developed using Simulink and SimDrivline could also be used as a generic, modular and flexible vehicle modeling platform to support the integration of powertrain design and control system optimization.

Eco-Trajectory Planning with Consideration of Queue along Congested Corridor for Hybrid Electric Vehicles

2019 ◽  
Vol 2673 (9) ◽  
pp. 277-286 ◽  
Author(s):  
Zhen Yang ◽  
Yiheng Feng ◽  
Xun Gong ◽  
Ding Zhao ◽  
Jing Sun
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Trajectory Planning ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Urban Traffic ◽  
Vehicle Speed ◽  
Speed Profile ◽  
Driving Model ◽  
Hybrid Electric

At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.

scholarly journals Research on innovative plug-in hybrid electric vehicle comprehensive energy consumption evaluation method based on statistic energy consumption

2021 ◽  
Vol 104 (4) ◽  
pp. 003685042110502
Author(s):  
Xinbo Chen ◽  
Jian Zhong ◽  
Feng Sha ◽  
Zaimin Zhong
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Evaluation Method ◽  
The United States ◽  
Specific Power ◽  
The European Union ◽  
Hybrid Electric

The plug-in hybrid electric vehicle not only has the advantages of low emissions from electric vehicles, but also takes advantage of the high specific energy and high specific power of petroleum fuels, which can significantly improve the emissions and fuel economy of traditional vehicles. Studying its comprehensive energy consumption evaluation method is an important part of analyzing the economics of plug-in hybrid electric vehicles. This paper first puts forward the concept of statistical energy consumption and then proposes an innovative calculation method of plug-in hybrid electric vehicle energy consumption based on statistical energy consumption by referring to and analyzing the energy consumption test regulations of the United States, the European Union, and China. Given the two use case assumptions of charge depleting mode priority and charge sustaining mode only, considering the fuel consumption and the energy consumption that converts electrical energy consumption to fuel consumption, the probability density function of travel mileage distribution and energy consumption is derived. Finally, the interpretation and analysis of statistical energy consumption evaluation results are carried out.

Impact of Motor Size & Efficiency on Acceleration, Fuel Consumption & Emissions of Split-Axle Through-the-Road Parallel Hybrid Electric Vehicle

2014 ◽  
Vol 663 ◽  
pp. 498-503 ◽  
Author(s):  
Saiful A. Zulkifli ◽  
Syaifuddin Mohd ◽  
Nordin B. Saad ◽  
A. Rashid A. Aziz
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Hybrid Vehicles ◽  
The Road ◽  
Parallel Hybrid Electric Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Improved Performance

A split-axle parallel hybrid drive-train with in-wheel motors allows for existing combustion-engine-driven vehicles to be converted into a hybrid vehicle with minor mechanical modification, resulting in a retrofit-conversion hybrid electric vehicle (HEV). This is achieved by placing electric motors in the hub of the otherwise non-driven wheels. Due to the wheel hub’s size constraint, the allowable size and power of the electric in-wheel motor that can be installed is severely restricted to less than 10 kW per wheel, which raises the concern of lack of improved performance compared to the original vehicle. This work analyzes the influence of motor sizing and efficiency on acceleration performance, fuel consumption and emission levels of three different converted hybrid vehicles, through simulation. Results provide insight into sensitivity of different-sized vehicles with varying-size engines, to the size and efficiency of the retrofitted electric motor.

Multiple-Objective Optimal Control of Hybrid Electric Vehicle

2013 ◽  
Vol 753-755 ◽  
pp. 1659-1664
Author(s):  
Jun Yan
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Optimal Control Strategy ◽  
Parallel Hybrid Electric Vehicle ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

To reduce the fuel consumption and exhaust (HC, CO) emissions of parallel hybrid electric vehicle, the control strategy of the hybrid electric vehicle is studied in this paper. First it briefly analyzes the structure and working principle of the parallel hybrid electric vehicle drive system. Then a cost function is proposed which explains the fuel consumption and emissions. According to the minimum principle the minimum of the cost function can be got, consequently, the optimal control strategy can be obtained. Furthermore, in order to verify the effectiveness of the optimal control strategy, in MATLAB environment, it establishes a dynamic simulation model for hybrid electric vehicles. Through a comparative study between the optimal control strategy on and the traditional rules control strategy, the results of experiment it reveals that the optimal control strategy can effectively reduces fuel consumption and emissions of hybrid electric vehicles.

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