scholarly journals Charge and discharge characteristics of different types of batteries on a hybrid electric vehicle model and selection of suitable battery type for electric vehicles

2019 ◽  
pp. 62-70 ◽  
Author(s):  
Yunus emre Ekici ◽  
Nusret Tan
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Vehicle Model ◽  
Discharge Characteristics ◽  
Different Types ◽  
Hybrid Electric ◽  
Selection Of

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.

scholarly journals Real-Time Co-optimization of Vehicle Route and Speed Using Generic Algorithm for Improved Fuel Economy

2019 ◽  
Vol 141 (03) ◽  
pp. S08-S15
Author(s):  
Guoming G. Zhu ◽  
Chengsheng Miao
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Autonomous Vehicles ◽  
Hybrid Electric Vehicle ◽  
High Efficiency ◽  
Combustion Engine ◽  
Cruise Control ◽  
Vehicle Performance ◽  
Hybrid Electric

Making future vehicles intelligent with improved fuel economy and satisfactory emissions are the main drivers for current vehicle research and development. The connected and autonomous vehicles still need years or decades to be widely used in practice. However, some advanced technologies have been developed and deployed for the conventional vehicles to improve the vehicle performance and safety, such as adaptive cruise control (ACC), automatic parking, automatic lane keeping, active safety, super cruise, and so on. On the other hand, the vehicle propulsion system technologies, such as clean and high efficiency combustion, hybrid electric vehicle (HEV), and electric vehicle, are continuously advancing to improve fuel economy with satisfactory emissions for traditional internal combustion engine powered and hybrid electric vehicles or to increase cruise range for electric vehicles.

Design and Analysis of a Series Hybrid Electric Vehicle for Indian Conditions

2012 ◽  
Author(s):  
C. S. Nanda Kumar ◽  
Shankar C. Subramanian
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Electric Motor ◽  
Hybrid Electric Vehicle ◽  
Traction Force ◽  
Drive System ◽  
Maximum Speed ◽  
Performance Requirements ◽  
Series Hybrid Electric Vehicle ◽  
Hybrid Electric

Electric and hybrid vehicles are emerging rapidly in the automotive market as alternatives to the traditional Internal Combustion Engine (ICE) driven vehicles to meet stringent emission standards, environmental and energy concerns. Recently, Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) have been introduced in many countries including India. One configuration of a HEV is the Series Hybrid Electric Vehicle (SHEV). The design and analysis of the drive system of a SHEV under Indian conditions is the focus of this paper. In conventional vehicles, the ICE is the power source that drives the vehicle. The energy from the ICE is distributed to the wheels through the transmission, which is then used to generate the traction force at the tyre-road interface. In a HEV, both the engine and the electric motor provide the energy to drive the vehicle. In a SHEV, the energy generated by the electric motor is transmitted through the transmission to meet the torque demand at the wheels. Based on the driver’s acceleration demand and the state of charge of the battery, the controller manages the ICE, the generator and the battery to supply the required energy to the motor. The motor finally develops the required drive torque to generate the traction force at the wheels to meet the vehicle drive performance requirements like gradeability, acceleration and maximum speed. The objective of this paper is to discuss the design of the drive system of a SHEV. This involves the calculation of the power specifications of the electric motor based on the vehicle drive performance requirements. The equations for performing these calculations are presented. The procedure is then demonstrated by considering a typical Indian commercial vehicle along with its typical vehicle parameter values. A simulation study has also been performed by considering the Indian drive cycle to demonstrate the energy savings obtained by the use of a SHEV.

Optimal Selection of Equivalence Factors for ECMS in Mild Hybrid Electric Vehicles

2021 ◽  
Author(s):  
Shailesh Hegde ◽  
Angelo Bonfitto ◽  
Hadi Rahmeh ◽  
Nicola Amati ◽  
Andrea Tonoli
Keyword(s):  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Shooting Method ◽  
Hybrid Electric Vehicles ◽  
Optimal Solution ◽  
Pollutant Emissions ◽  
Hybrid Electric ◽  
Mild Hybrid ◽  
Selection Of

Abstract The increasing stringent emissions regulation over the years have shifted the focus of automotive industry towards more efficient fuel economy solutions. One such solution is Hybrid electric architecture, which is able to improve the fuel economy and consequently cutting down emissions. A well known control strategy to solve optimization problem for energy management of Hybrid electric vehicles is ECMS (Equivalent Consumption Minimization Strategy). Finding the best control parameters (equivalence factors) of this strategy may become quite involved. This paper proposes a method for the selection of the optimal equivalence factors, for charging and discharging, by applying genetic algorithm in the case of a P0 mild hybrid electric vehicle. This method is a systematic and deterministic way to guarantee an optimal solution with respect to the trial and error method. The proposed ECMS is compared to a technique available in literature, known as the shooting method, which relies only on one equivalence factor for discharging. It is demonstrated that the performance in terms of pollutant emissions are comparable. However, ECMS with GA always guarantees an optimal solution even in the case of heavy accessory load, when shooting method is not valid anymore, as it does not guarantee a charge sustaining condition.

Multi-Layer Mini-Channel and Ribbed Mini-Channel Based High Performance Cooling Configurations for Automotive Inverters—Part A: Design and Evaluation

2013 ◽  
Vol 5 (3) ◽  
Author(s):  
Pritish R. Parida ◽  
Srinath V. Ekkad ◽  
Khai Ngo
Keyword(s):  
Power Control ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
High Performance ◽  
Heat Dissipation ◽  
Cooling System ◽  
Control Unit ◽  
Consumer Products ◽  
Hybrid Electric

Necessitated by the dwindling supply of petroleum resources, various new automotive technologies have been actively developed from the perspective of achieving energy security and diversifying energy sources. Hybrid electric vehicles and electric vehicles are a few such examples. Such diversification requires the use of power control units essentially for power control, power conversion, and power conditioning applications such as variable speed motor drives (dc–ac conversion), dc–dc converters and other similar devices. The power control unit of a hybrid electric vehicle or electric vehicle is essentially the brain of the hybrid system as it manages the power flow between the electric motor generator, battery and gas engine. Over the last few years, the performance of this power control unit has been improved and size has been reduced to attain higher efficiency and performance, causing the heat dissipation as well as heat density to increase significantly. Efforts are constantly being made to reduce this size even further. As a consequence, a better high performance cooler/heat exchanger is required to maintain the active devices temperature within optimum range. Cooling schemes based on multiple parallel channels are a few solutions which have been widely used to dissipate transient and steady concentrated heat loads and can be applied to existing cooling system with minor modifications. The aim of the present study has therefore been to study the various cooling options based on mini-channel and rib-turbulated mini-channel cooling for application in a hybrid electric vehicle and other similar consumer products, and perform a parametric and optimization study on the selected designs. Significant improvements in terms of thermal performance, reduced overall pressure drop, and volume reduction have been shown both experimentally and numerically. This paper is the first part in a two part submission and focuses on the design and evaluation of mini-channel and rib-turbulated mini-channel cooling configurations. The second part of this paper discusses the manufacturing and testing of the cooling device.

Development of a software platform for a plug-in hybrid electric vehicle simulator

2012 ◽  
Vol 2 (1) ◽  
Author(s):  
Athanasios Karlis ◽  
Eric Bibeau ◽  
Paul Zanetel ◽  
Zelon Lye
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Alternative Energy ◽  
Hybrid Electric Vehicle ◽  
Energy Mix ◽  
Electricity Use ◽  
Transportation Sector ◽  
Battery Capacity ◽  
Vehicle Simulator ◽  
Hybrid Electric

AbstractElectricity use for transportation has had limited applications because of battery storage range issues, although many recent successful demonstrations of electric vehicles have been achieved. Renewable biofuels such as biodiesel and bioethanol also contribute only a small percentage of the overall energy mix for mobility. Recent advances in hybrid technologies have significantly increased vehicle efficiencies. More importantly, hybridization now allows a significant reduction in battery capacity requirements compared to pure electric vehicles, allowing electricity to be used in the overall energy mix in the transportation sector. This paper presents an effort made to develop a Plug-in Hybrid Electric Vehicle (PHEV) platform that can act as a comprehensive alternative energy vehicle simulator. Its goal is to help in solving the pressing needs of the transportation sector, both in terms of contributing data to aid policy decisions for reducing fossil fuel use, and to support research in this important area. The Simulator will allow analysing different vehicle configurations, and control strategies with regards to renewable and non-renewable fuel and electricity sources. The simulation platform models the fundamental aspects of PHEV components, that is, process control, heat transfer, chemical reactions, thermodynamics and fluid properties. The outcomes of the Simulator are: (i) determining the optimal combination of fuels and grid electricity use, (ii) performing greenhouse gas calculations based on emerging protocols being developed, and (iii) optimizing the efficient and proper use of renewable energy sources in a carbon constrained world.

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