scholarly journals A DCT-Based Driving Cycle Generation Method and Its Application for Electric Vehicles

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Cheng Lin ◽  
Li Zhao ◽  
Xingqun Cheng ◽  
Wenwei Wang
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Internal Combustion Engines ◽  
Renewable Energy Sources ◽  
Driving Cycle ◽  
Combustion Engines ◽  
Zero Emission ◽  
Working Status ◽  
Frequency Sequence ◽  
Management Algorithms

Nowadays, many widely used driving cycle (DC) representing and generating methods are designed for traditional vehicles with internal combustion engines (ICE). The real-world driving is viewed as a sequence of acceleration, cruise, deceleration, and idle modes. The emission and fuel consumption in each period should be taken into account carefully. However, for electric vehicles (EVs), most of them are powered by low or zero-emission renewable energy sources. The working status and energy management algorithms of them are very different from traditional vehicles. To facilitate the EV design, we proposed a novel DC representing and construction method to generate DCs for EVs. The whole driving route is divided into several length-fixed segments and each of these segments is converted into a frequency sequence. After doing that, we can adjust the frequency and amplitude of the generated driving cycle directly. The experiment results showed that the proposed method was effective and convenient.

Study and Investigation of Energy Management Techniques Used in Electric/Hybrid Electric Vehicles

2021 ◽  
Vol 54 (4) ◽  
pp. 599-606
Author(s):  
Punyavathi Ramineni ◽  
Alagappan Pandian
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Internal Combustion Engines ◽  
Hybrid Electric Vehicles ◽  
Vital Role ◽  
Combustion Engines ◽  
Key Factor ◽  
Hybrid Electric ◽  
And Control ◽  
Intelligent Controllers

Many pollution-related issues are raising due to the usage of conventional internal combustion engines (ICEs) vehicles. Electric Vehicles/ Hybrid electric vehicles (EVs/HEVs) are the finest solutions to overcome those problems associated with ICE-based vehicles. The EVs are introduced with a signal energy source (SES), which is not a successful attempt, especially during transient vehicles, driving, etc. Multiple energy sources (MES) EVs are introduced to attain better performance than the SES vehicles, which is obtained by combining two sources like battery/fuel cells, ultracapacitor. In this contest, energy management (EMNG) plays a vital role in sharing the load to the sources as per the EVs requirement. In the case of MES-based EVs, the controller always plays a significant role in the related EMNG system because it is the key factor in improving vehicle efficiency. In this article, a study has mainly been done related to several conventional, intelligent controllers and control algorithms to do the proper EMNG between sources present in the EV.

INCUMBENCY AND THE DISRUPTIVE REGULATOR: THE CASE OF ELECTRIC VEHICLES IN CALIFORNIA

2004 ◽  
Vol 08 (04) ◽  
pp. 339-354 ◽  
Author(s):  
ALAN PILKINGTON ◽  
ROMANO DYERSON
Keyword(s):  
Electric Vehicles ◽  
Internal Combustion Engines ◽  
Past Century ◽  
Combustion Engines ◽  
Strategic Responses ◽  
The Past ◽  
Path Dependencies ◽  
Zero Emission ◽  
Complementary Assets ◽  
Emission Legislation

For much of the past century, the automobile sector has been dominated by a handful of oligopolistic firms, protected through path dependencies and the build up of complementary assets. But that very dominance built upon years of experience and translated into the periodic release of incrementally innovative new car designs, may now be threatened by the actions of regulators in California and elsewhere, in mandating emission friendly cars. The biggest challenge in this area has been the demand for zero emission vehicles resulting from Californian regulations. Zero emission legislation mandates the use of technologies radically different from those used in the development of internal combustion engines. Such technology acts in a disruptive manner on the existing skills base of the automobile firms, negating some of the benefits of incumbency. With little or no experience of the systems needed to develop a viable electric vehicle — batteries, electric motors and controllers — the established automobile manufacturers have struggled with a strategic question: how to incorporate disruptive elements into a mature organisation. This paper explores the nature of the regulatory threat and the strategic responses generated by the automobile firms.

scholarly journals QoE-Aware Smart Home Energy Management Considering Renewables and Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2304 ◽  
Author(s):  
Mingfu Li ◽  
Guan-Yi Li ◽  
Hou-Ren Chen ◽  
Cheng-Wei Jiang
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Smart Home ◽  
Control Algorithm ◽  
Renewable Energy Sources ◽  
Peak Load ◽  
Electricity Bill ◽  
Home Energy Management ◽  
Smart Appliance ◽  
User Comfort

To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE.

scholarly journals Smart ceramic materials for homogeneous combustion in internal combustion engines: A review

2009 ◽  
Vol 13 (3) ◽  
pp. 153-163 ◽  
Author(s):  
Kannan Chidambaram ◽  
Tamilporai Packirisamy
Keyword(s):  
Combustion Chamber ◽  
Internal Combustion Engines ◽  
Porous Ceramic ◽  
Ceramic Materials ◽  
Combustion Engines ◽  
Emission Level ◽  
Engine Cylinder ◽  
Homogeneous Combustion ◽  
Zero Emission ◽  
Porous Ceramic Materials

The advantages of using ceramics in advanced heat engines include increased fuel efficiency due to higher engine operating temperatures, more compact designs with lower capacity cooling system. Future internal combustion engines will be characterized by near zero emission level along with low specific fuel consumption. Homogenous combustion which realized inside the engine cylinder has the potential of providing near zero emission level with better fuel economy. However, the accomplishment of homogeneous combustion depends on the air flow structure inside the combustion chamber, fuel injection conditions and turbulence as well as ignition conditions. Various methods and procedures are being adopted to establish the homogeneous combustion inside the engine cylinder. In recent days, porous ceramic materials are being introduced inside the combustion chamber to achieve the homogeneous combustion. This paper investigates the desirable structures, types, and properties of such porous ceramic materials and their positive influence on the combustion process.

Analysis of Current Hybrid-Electric Automobile Drivetrains and Proposal of an Alternative Powertrain

2020 ◽  
Author(s):  
Andrew Ahn ◽  
Thomas S. Welles ◽  
Benjamin Akih-Kumgeh
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Internal Combustion Engines ◽  
Hybrid Electric Vehicles ◽  
Global Climate ◽  
Low Cost ◽  
Fuel Efficiency ◽  
Combustion Engines ◽  
Hybrid Electric ◽  
Hybrid Configuration

Abstract Byproducts of fossil fuel combustion contribute to negative changes in the global climate. Specifically, emissions from automobiles are a major source of greenhouse gas pollution. Efforts to minimize these harmful emissions have led to the development and sustained improvement of hybrid drivetrains in automobiles. Despite many advancements, however, hybrid systems still face substantial challenges which bear on their practicality, performance, and competitive disadvantage in view of the low cost of today’s traditional internal combustion engines. These imperfections notwithstanding, hybrid electric vehicles have the potential to play significant roles in the future as cleaner transportation solutions. Actualization of this potential will depend on the ability of hybrid-electric vehicles to minimize their disadvantages while increasing their positive features relative to traditional combustion engines. This research investigates current hybrid electric architectures in automobiles with the aim of suggesting an alternative, more efficient hybrid configuration that utilizes current technology. This is completed by utilizing an iterative design process to compare how various components of existing hybrids can be combined and/or improved to develop a single, efficient and cohesive system that performs comparably to or surpasses existing ones in fuel efficiency and low emissions in all driving conditions. A critical and comparative analysis is provided based on current hybrid-electric vehicle architectures as well as a plausible alternative.

scholarly journals A Neural Network Fuzzy Energy Management Strategy for Hybrid Electric Vehicles Based on Driving Cycle Recognition

2020 ◽  
Vol 10 (2) ◽  
pp. 696
Author(s):  
Qi Zhang ◽  
Xiaoling Fu
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Membership Function ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Fuzzy Energy

Aiming at the problems inherent in the traditional fuzzy energy management strategy (F-EMS), such as poor adaptive ability and lack of self-learning, a neural network fuzzy energy management strategy (NNF-EMS) for hybrid electric vehicles (HEVs) based on driving cycle recognition (DCR) is designed. The DCR was realized by the method of neural network sample learning and characteristic parameter analysis, and the recognition results were considered as the reference input of the fuzzy controller with further optimization of the membership function, resulting in improvement in the poor pertinence of F-EMS driving cycles. The research results show that the proposed NNF-EMS can realize the adaptive optimization of fuzzy membership function and fuzzy rules under different driving cycles. Therefore, the proposed NNF-EMS has strong robustness and practicability under different driving cycles.

scholarly journals Research on Energy Management Strategies of Extended-Range Electric Vehicles Based on Driving Characteristics

2020 ◽  
Vol 11 (3) ◽  
pp. 54 ◽  
Author(s):  
Yuanbin Yu ◽  
Junyu Jiang ◽  
Zhaoxiang Min ◽  
Pengyu Wang ◽  
Wangsheng Shen
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Control Strategies ◽  
Management Strategies ◽  
Principal Component ◽  
Driving Cycle ◽  
Control Parameters ◽  
Energy Management Strategy ◽  
Extended Range

The extended-range electric vehicle (E-REV) can solve the problems of short driving range and long charging time of pure electric vehicles, but it is necessary to control the engine working points and allocate the power of the energy sources reasonably. In order to improve the fuel economy of the vehicle, an energy management strategy (EMS) that can adapt to the daily driving characteristics of the driver and adjust the control parameters online is proposed in this paper. Firstly, through principal component analysis (PCA) and iterative self-organizing data analysis techniques algorithm (ISODATA) of historical driving data, a typical driving cycle which can describe driving characteristics of the driver is constructed. Then offline optimization of control parameters by adaptive simulated annealing under each typical driving cycle and online recognition of driving cycles by extreme learning machine (ELM) are applied to the adaptive multi-workpoints energy management strategy (A-MEMS) of E-REV. In the end, compared with traditional rule-based control strategies, A-MEMS achieves good fuel-saving and emission-reduction result by simulation verification, and it explores a new and feasible solution for the continuous upgrade of the EMS.

scholarly journals The Impact of Powering an Engine with Fuels from Renewable Energy Sources including its Software Modification on a Drive Unit Performance Parameters

2019 ◽  
Vol 11 (23) ◽  
pp. 6585 ◽  
Author(s):  
Markiewicz ◽  
Muślewski
Keyword(s):  
Renewable Energy ◽  
Internal Combustion Engines ◽  
Combustion Engine ◽  
Renewable Energy Sources ◽  
Internal Combustion ◽  
Energy Sources ◽  
Exhaust Emission ◽  
Combustion Engines ◽  
Performance Parameters ◽  
The Impact

The application of fuels from renewable energy sources for combustion engine powering involves a great demand for this kind of energy while its production infrastructure remains underdeveloped. The use of this kind of fuel is supposed to reduce the emission of greenhouse gases and the depletion of natural resources and to increase the share of renewable energy sources in total energy consumption and thus support sustainable development in Europe. This study presents the results of research on selected performance parameters of transport by internal combustion engines including: power, torque, the emission of sound generated by the engine, the content of exhaust components (oxygen O2, carbon monoxide CO, carbon dioxide CO2, nitrogen dioxide NO2), and the content of particulate matter (PM) in exhaust emission. Three self-ignition engines were tested. The fuel injection controllers of the tested internal combustion engines were additionally adjusted by increasing the fuel dose and the load of air. The material used in the tests were mixtures of diesel oil and fatty acid methyl esters of different concentration. A statistical analysis was performed based of the results. The purpose of the work was to develop a resulting model for assessing the operation of engines fueled with biofuel and diesel mixtures while changing the vehicle's computer software. A computer simulation algorithm was also developed for the needs of the tests which was used to prognose the state of the test results for variable input parameters.

Sign in / Sign up

Export Citation Format

Share Document