scholarly journals Development of Transmission Systems for Parallel Hybrid Electric Vehicles

2019 ◽  
Vol 9 (8) ◽  
pp. 1538 ◽  
Author(s):  
Po-Tuan Chen ◽  
Ping-Hao Pai ◽  
Cheng-Jung Yang ◽  
K. David Huang
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Gear Ratio ◽  
Parallel Hybrid ◽  
Matching Design ◽  
Hybrid Electric ◽  
Optimal Efficiency ◽  
And Performance

This study investigated the matching designs between a power integration mechanism (PIM) and transmission system for single-motor parallel hybrid electric vehicles. The optimal matching design may lead to optimal efficiency and performance in parallel hybrid vehicles. The Simulink/Simscape environment is used to model the powertrain system of parallel hybrid electric vehicles, which the characteristics of the PIM, location of the gearbox at the driveline, and design of the gear ratio of a gearbox influenced. The matching design principles for torque-coupled–type PIM (TC-PIM) parameters and the location of the gearbox are based on the speed range of the electric motor and the internal combustion engine. The parameters of the TC-PIM (i.e., k 1 and k 2 ) are based on the k ratio theory. Numerical simulations of an extra-urban driving cycle and acceleration tests reveal that a higher k r a t i o has greater improved power-assist ability under a pre-transmission architecture. For example, a k r a t i o of 1.6 can improve the power-assist ability by 8.5% when compared with a k r a t i o of 1. By using an appropriate gear ratio and k r a t i o , the top speed of a hybrid electric vehicle is enhanced by 9.3%.

scholarly journals Comparisons of Real-World Vehicle Energy Efficiency with Dynamometer-Based Ratings and Simulation Models

2021 ◽  
Vol 12 (4) ◽  
pp. 161
Author(s):  
Karim Hamza ◽  
Kang-Ching Chu ◽  
Matthew Favetti ◽  
Peter Keene Benoliel ◽  
Vaishnavi Karanam ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Real World ◽  
Hybrid Electric Vehicle ◽  
Energy Intensity ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Simulation Models ◽  
Hybrid Electric

Software tools for fuel economy simulations play an important role during design stages of advanced powertrains. However, calibration of vehicle models versus real-world driving data faces challenges owing to inherent variations in vehicle energy efficiency across different driving conditions and different vehicle owners. This work utilizes datasets of vehicles equipped with OBD/GPS loggers to validate and calibrate FASTSim (software originally developed by NREL) vehicle models. The results show that window-sticker ratings (derived from dynamometer tests) can be reasonably accurate when averaged across many trips by different vehicle owners, but successfully calibrated FASTSim models can have better fidelity. The results in this paper are shown for nine vehicle models, including the following: three battery-electric vehicles (BEVs), four plug-in hybrid electric vehicles (PHEVs), one hybrid electric vehicle (HEV), and one conventional internal combustion engine (CICE) vehicle. The calibrated vehicle models are able to successfully predict the average trip energy intensity within ±3% for an aggregate of trips across multiple vehicle owners, as opposed to within ±10% via window-sticker ratings or baseline FASTSim.

scholarly journals Series-Parallel Hybrid Electric Vehicle Parameter Analysis using MATLAB

2021 ◽  
Vol 9 (10) ◽  
pp. 421-428
Author(s):  
Richik Ray
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Matlab Simulink ◽  
Parallel Hybrid Electric Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric

Abstract: In this paper, a MATLAB based Simulink model of a Series-Parallel Hybrid Electric Vehicle is presented. With the advent of Industry 4.0, the usage of Big Data, Machine Learning, Internet of Things, Artificial Intelligence, and similar groundbreaking domains of technology have usurped manual supervision in industrial as well as personal scenarios. This is aided by the drastic shift from orthodox and conventional Internal Combustion Engine based vehicles fuelled by fossil fuels in the order of petrol, diesel, etc., to fully functional electric vehicles developed by renowned companies, for example Tesla. Alongside 100% electric vehicles are hybrid vehicles that function on a system based on the integration of the conventional ICE and the modern Electric Propulsion System, which is referred to as the Hybrid Vehicle Drivetrain. Designs for modern HEVs and EVs are developed on computer software where simulations are run and all the essential parameters for the vehicle’s performance and sustainability are run and observed. This paper is articulated to discuss the parameters of a series-parallel HEV through an indepth MATLAB Simulink design, and further the observations are presented. Keywords: ICE (Internal Combustion Engine), HEV (Hybrid Electric Vehicle), Drivetrain, MATLAB, Simulink, PSD (Power Split Device), Vehicle Dynamics, SOC (State-of-Charge)

scholarly journals Torque Split Strategy for Parallel Hybrid Electric Vehicles with an Integrated Starter Generator

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Zhumu Fu ◽  
Aiyun Gao ◽  
Xiaohong Wang ◽  
Xiaona Song
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicles ◽  
Fuzzy Logic Controller ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Torque Control ◽  
Torque Control Strategy ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Starter Generator

This paper presents a torque split strategy for parallel hybrid electric vehicles with an integrated starter generator (ISG-PHEV) by using fuzzy logic control. By combining the efficiency map and the optimum torque curve of the internal combustion engine (ICE) with the state of charge (SOC) of the batteries, the torque split strategy is designed, which manages the ICE within its peak efficiency region. Taking the quantified ICE torque, the quantified SOC of the batteries, and the quantified ICE speed as inputs, and regarding the output torque demanded on the ICE as an output, a fuzzy logic controller (FLC) with relevant fuzzy rules has been developed to determine the optimal torque distribution among the ICE, the ISG, and the electric motor/generator (EMG) effectively. The simulation results reveal that, compared with the conventional torque control strategy which uses rule-based controller (RBC) in different driving cycles, the proposed FLC improves the fuel economy of the ISG-PHEV, increases the efficiency of the ICE, and maintains batteries SOC within its operation range more availably.

scholarly journals Intelligent Control of Parallel Hybrid Electric Vehicles

1999 ◽  
Author(s):  
Bradley Glenn ◽  
Gregory Washington ◽  
Giorgio Rizzoni
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Logic Controller ◽  
Hybrid Electric Vehicles ◽  
Conventional Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Reduce Emissions

Abstract Currently Hybrid Electric Vehicles (HEV) are being considered as an alternative to conventional automobiles in order to improve efficiency and reduce emissions. To demonstrate the potential of an advanced control strategy for HEV’s, a fuzzy logic control strategy has been developed and implemented in simulation in the National Renewable Energy Laboratory’s simulator Advisor (version 2.0.2). The Fuzzy Logic Controller (FLC) utilizes the electric motor in a parallel hybrid electric vehicle (HEV) to force the ICE (66KW Volkswagen TDI) to operate at or near its peak point of efficiency or at or near its best fuel economy. Results with advisor show that the vehicle with the Fuzzy Logic Controller can achieve (56) mpg in the city, while maintaining a state of charge of .68 for the battery pack, compared to (43) mpg for a conventional vehicle. This scheme has also brought to light various rules of thumb for the design and operation of HEV’s.

Optimization of Component Sizes in Parallel Hybrid Electric Vehicles via Genetic Algorithms

2005 ◽  
Author(s):  
Morteza Montazeri-Gh ◽  
Amir Poursamad
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Driving Cycles ◽  
Component Sizing ◽  
Driving Pattern ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

This paper describes the optimization of the parallel hybrid electric vehicle (HEV) component sizing using a genetic algorithm approach. The optimization process is performed over three different driving cycles including the European ECE-EUDC, American FTP and TEH-CAR cycles in order to investigate the influence of the driving pattern on the optimal HEV component sizes. Hybrid Electric Vehicles are considered as a solution to the world’s need for cleaner and more fuel-efficient vehicles. HEVs use a combination of an internal combustion engine and an electric motor to propel the vehicle. Proper execution of a successful HEV design requires optimal sizing of its key mechanical and electrical components. In this paper, genetic algorithm is used as the optimization approach to find the best size of internal combustion engine, electric motor and energy storage system. The objective is minimization of fuel consumption and emissions while vehicle performances, like acceleration and gradeability are defined as constraints. These constraints are handled using penalty functions. Simulation results reveal that the HEV optimal component sizing is independent from the driving pattern. However, the amount of fuel use and emissions are extremely dependent on the driving cycles. In addition, the results show, while the performance constraints are within the standard criteria, the reduction in fuel consumption and emissions are achieved.

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

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.

Sign in / Sign up

Export Citation Format

Share Document