Study of the Fuel Consumption of ECMS Applied to a HEV

2013 ◽  
Vol 712-715 ◽  
pp. 2173-2178
Author(s):  
Ping Sun ◽  
Xiu Min Yu ◽  
Wei Dong ◽  
Ling He
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Energy Flow ◽  
Hybrid Electric Vehicle ◽  
Fuel Efficiency ◽  
The Other ◽  
Power Sources ◽  
Analytical Formulation ◽  
Multiple Power

Hybrid electric vehicle (HEV) is integrated with the engine, the motor and the battery and so on. HEV has a significantly better fuel efficiency compared with conventional vehicles due to its multiple power sources. To evaluate fuel economy, HEV and its subsystem modeling methodologies were provided through the analysis of energy flow. The Equivalent Consumption Minimization Strategy (ECMS) was built based on the prototype. The ECMS implementation analytical formulation was developed. The equivalency factor, one for charging and the other for discharging, each of them was different during a driving cycle. In a certain drive, only a subset of them generates a trend close to zero, which indicates charge-sustainability.

An adaptive equivalent consumption minimization strategy considering catalyst temperature for plug-in hybrid electric vehicle

2021 ◽  
pp. 095440702110434
Author(s):  
Tao Deng ◽  
Ke Zhao ◽  
Haoyuan Yu
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Test Procedure ◽  
Catalyst Temperature ◽  
Equivalent Factor ◽  
Simulation Results ◽  
Hybrid Electric ◽  
Equivalent Consumption Minimization Strategy

In the process of sufficiently considering fuel economy of plug-in hybrid electric vehicle (PHEV), the working time of engine will be reduced accordingly. The increased frequency that the three-way catalytic converter (TWCC) works in abnormal operating temperature will lead to the increasing of emissions. This paper proposes the equivalent consumption minimization strategy (ECMS) to ensure the catalyst temperature of PHEV can work in highly efficient areas, and the influence of catalyst temperature on fuel economy and emissions is considered. The simulation results show that the fixed equivalent factor of ECMS has great limitations for the underutilized battery power and the poor fuel economy. In order to further reduce fuel consumption and keep the emission unchanged, an equivalent factor map based on initial state of charge (SOC) and vehicle mileage is established by the genetic algorithm. Furthermore, an Adaptive changing equivalent factor is achieved by using the following strategy of SOC trajectory. Ultimately, adaptive equivalent consumption minimization strategy (A-ECMS) considering catalyst temperature is proposed. The simulation results show that compared with ordinary ECMS, HC, CO, and NOX are reduced by 14.6%, 20.3%, and 25.8%, respectively, which effectively reduces emissions. But the fuel consumption is increased by only 2.3%. To show that the proposed method can be used in actual driving conditions, it is tested on the World Light Vehicle Test Procedure (WLTC).

scholarly journals Modeling and energy management strategy research of a power-split hybrid electric vehicle

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096262
Author(s):  
Yupeng Zou ◽  
Ruchen Huang ◽  
Xiangshu Wu ◽  
Baolong Zhang ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Research Work ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Power Split ◽  
Hybrid Electric ◽  
The Impact

A power-split hybrid electric vehicle with a dual-planetary gearset is researched in this paper. Based on the lever analogy method of planetary gearsets, the power-split device is theoretically modeled, and the driveline simulation model is built by using vehicle modeling and simulation toolboxes in MATLAB. Six operation modes of the vehicle are discussed in detail, and the kinematic constraint behavior of power sources are analyzed. To verify the rationality of the modeling, a rule-based control strategy (RB) and an adaptive equivalent consumption minimization strategy (A-ECMS) are designed based on the finite state machine and MATLAB language respectively. In order to demonstrate the superiority of A-ECMS in fuel-saving and to explore the impact of different energy management strategies on emission, fuel economy and emission performance of the vehicle are simulated and analyzed under UDDS driving cycle. The simulation results of the two strategies are compared in the end, shows that the modeling is rational, and compared with RB strategy, A-ECMS ensures charge sustaining better, enables power sources to work in more efficient areas, and improves fuel economy by 8.65%, but significantly increases NOx emissions, which will be the focus of the next research work.

Study the Impact of Driver’s Behavior on the Energy Efficiency of Hybrid Electric Vehicles

2013 ◽  
Author(s):  
Lei Feng ◽  
Bo Chen
Keyword(s):  
Energy Loss ◽  
Electric Vehicle ◽  
Simulation Study ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Fuel Efficiency ◽  
Aggressive Driving ◽  
Driving Cycles ◽  
Hybrid Electric ◽  
The Impact

This paper investigates the impact of driver’s behavior on the fuel efficiency of a hybrid electric vehicle (HEV) and its powertrain components, including engine, motor, and battery. The simulation study focuses on the investigation of power request, power output, energy loss, and operating region of powertrain components with the change of driver’s behavior. It is well known that a noticeable difference between the sticker number fuel economy and actual fuel economy will happen when a driver drives aggressively. To simulate aggressive driving, the input driving cycles are scaled from the baseline driving cycles to increase the level of acceleration/deceleration. With scaled aggressive driving cycles, the simulation result shows a significant change of HEV equivalent fuel economy. In addition, the high power demands of aggressive driving cause engine to operate within a higher fuel rate region. Furthermore, the engine is started and shut down frequently due to the large instantaneous power request peaks, which result in high energy loss. The simulation study of the impact of aggressive driving on the HEV fuel efficiency is conducted for a power-split hybrid electric vehicle using powertrain simulation and analysis software Autonomie developed by Argonne National Laboratory. The performance of the major powertrain components is analyzed when the HEV operates at different level of aggressiveness. The simulation results provide useful information to identify the major factors that need to be included in the vehicle control design to improve the fuel efficiency of HEVs under aggressive driving.

Importance of Vehicle Costs, Fuel Prices, and Fuel Efficiency in Hybrid Electric Vehicle Market Success

2000 ◽  
Vol 1738 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Danilo J. Santini ◽  
Philip D. Patterson ◽  
Anant D. Vyas
Keyword(s):  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Fuel Efficiency ◽  
Argonne National Laboratory ◽  
The United States ◽  
Fuel Price ◽  
Fuel Savings ◽  
Hybrid Electric ◽  
National Cooperative

Toyota’s introduction of a hybrid electric vehicle (HEV) named “Prius” in Japan and Honda’s proposed introduction of an HEV in the United States have generated considerable interest in the long-term viability of such fuel-efficient vehicles. A performance and cost projection model developed entirely at Argonne National Laboratory (ANL) is used to estimate costs. ANL staff developed fuel economy estimates by extending conventional vehicle modeling done primarily under the National Cooperative Highway Research Program. Together, these estimates are employed to analyze dollar costs versus benefits of two of many possible HEV technologies. Incremental costs and fuel savings are projected for a Prius-type low-performance hybrid (14.3-s 0 to 60 mph acceleration, Z60 time) and a higher-performance “mild” hybrid vehicle (11-s Z60 time). Each HEV is compared with a U.S. Toyota Corolla with automatic transmission (11-s Z60 time). The base incremental retail price range, projected a decade hence, is $3,200–$3,750, before considering battery replacement cost. Historical data are analyzed to evaluate the effect of fuel price on consumer preferences for vehicle fuel economy, performance, and size. The relationship among fuel price, the level of change in fuel price, and consumer attitude toward higher fuel efficiency also is evaluated. A recent survey on the value of higher fuel efficiency is presented and U.S. commercial viability of the hybrids is evaluated using discount rates of 20 percent and 8 percent. The analysis, with its current HEV cost estimates and current fuel savings estimates, implies that the U.S. market for such HEVs would be quite limited.

Modeling and Control of New Multi-Mode Plug-in Hybrid Electric Vehicle

2019 ◽  
Author(s):  
Abhinandan Raut ◽  
Suryaji Phalke ◽  
Diane Peters
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Powertrain ◽  
Power Sources ◽  
Full Size ◽  
Wide Range ◽  
Hybrid Electric ◽  
Multi Mode

Abstract Fuel economy and emission standards for internal combustion engine (ICE) vehicles lead to emergence of hybrid powertrain mechanisms. Hybrid powertrains can enable significant fuel economy improvements without sacrificing vehicle performance or utility. This requires optimization of engine operation, regenerative braking, and use of a wide range of possible combinations of engine and battery usage. The multi-mode hybrid powertrain in this paper combines many options to meet a complex driving requirement while maintaining the desired fuel economy. In this paper, a systematic design methodology is used to design a full-size hybrid vehicle with multiple components. This involves the modeling, simulation and development of optimal energy management strategy. This vehicle (full size car) has dual battery, dual fuel V6 engine with cylinder deactivation and bi-directional power flow in and from dual motor/generator. The design includes multiple gearboxes to connect these pieces. The vehicle model allows many degrees of freedom including various modes of operation depending upon the combination of degree of driver involvement, vehicle power requirement and optimized fuel economy resulting in automatic switching between modes. This model is tested for different Environmental Protection Agency (EPA) driving cycles. By integrating all components of this hybrid electric vehicle (HEV) and the highly coordinated energy management control system that performs optimum blending of torque, speed, and power from multiple power sources, the benefit from this hybridization is maximized.

scholarly journals Support vector machine–based driving cycle recognition for dynamic equivalent fuel consumption minimization strategy with hybrid electric vehicle

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401881102
Author(s):  
QIN Shi ◽  
Duoyang Qiu ◽  
Lin He ◽  
Bing Wu ◽  
Yiming Li
Keyword(s):  
Support Vector Machine ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Driving Cycle ◽  
Support Vector ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

For a great influence on the fuel economy and exhaust, driving cycle recognition is becoming more and more widely used in hybrid electric vehicles. The purpose of this study is to develop a method to identify the type of driving cycle in real time with better accuracy and apply the driving cycle recognition to minimize the fuel consumption with dynamic equivalent fuel consumption minimization strategy. The support vector machine optimized by the particle swarm algorithm is created for building driving cycle recognition model. Furthermore,the influence of the two parameters of window width and window moving velocity on the accuracy is also analyzed in online application. A case study of driving cycle in a medium-sized city is introduced based on collecting four typical driving cycle data in real vehicle test. A series of characteristic parameters are defined and principal component analysis is used for data processing. Finally, the driving cycle recognition model is used for equivalent fuel consumption minimization strategy with a parallel hybrid electric vehicle. Simulation results show that the fuel economy can improve by 9.914% based on optimized support vector machine, and the fluctuations of battery state of charge are more stable so that system efficiency and batter life are substantially improved.

scholarly journals Exploitation of a Particle Swarm Optimization Algorithm for Designing a Lightweight Parallel Hybrid Electric Vehicle

2021 ◽  
Vol 11 (15) ◽  
pp. 6833
Author(s):  
Matteo Spano ◽  
Pier Giuseppe Anselma ◽  
Daniela Anna Misul ◽  
Giovanni Belingardi
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Production Cost ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Power Sources

The dramatic global climate change has driven governments to drastically tackle pollutant emissions. In the transportation field, one of the technological responses has been powertrain electrification for passengers’ cars. Nevertheless, the large amount of possible powertrain designs does not help the development of an exhaustive sizing process. In this research, a multi-objective particle swarm optimization algorithm is proposed to find the optimal layout of a parallel P2 hybrid electric vehicle powertrain with the aim of maximizing fuel economy capability and minimizing production cost. A dynamic programming-based algorithm is used to ensure the optimal vehicle-level energy management. The results show that diverse powertrain layouts may be suggested when different weights are assigned to the sizing targets related to fuel economy and production cost, respectively. Particularly, upsizing the power sources and increasing the number of gears might be advised to enhance HEV fuel economy capability through the efficient exploitation of the internal combustion engine (ICE) operation. On the other hand, reduction of the HEV production cost could be achieved by downsizing the power sources and limiting the number of gears with respect to conventional ICE-powered vehicles thanks to the interaction between ICE and electric motor.

scholarly journals ANALYSIS OF EQUIVALENT FUEL SAVINGS OF ELECTRIC VEHICLES

2020 ◽  
Vol 20 ◽  
pp. 85-89
Author(s):  
A. Gavrilyk ◽  
M. Lemishko
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Fuel Cell Vehicle ◽  
Electric Cars ◽  
Advantages And Disadvantages ◽  
Equivalent Fuel ◽  
Equivalent Fuel Consumption

The development of electric vehicles in the near future is outlined, their general classification and problems of their use are given. The most common energy elements used to power electric traction electric motors are analyzed, their advantages and disadvantages are described. The analysis shows the most economical electric cars in 2018 and describes their traction and speed characteristics. The peculiarities of methodology for determining fuel economy for hybrid vehicles (PHEV - plugin hybrid electric vehicle) and for vehicles running on alternative fuel type (NGV-natural gas vehicle; FCV-fuel cell vehicle) are revealed and the possibility of its improvement is revealed. Methodological bases of estimation of fuel economy of electric vehicles are developed. This will allow potential buyers, owners or economists of the trucking companies to objectively estimate the equivalent fuel consumption and successfully choose one or the other brand of electric vehicle. An algorithm for determining the equivalent fuel economy of electric vehicles was developed and described taking into account the energy price policy for different countries of the world.It is concluded that lithiumion batteries have become the most widespread, as the feeding elements of electric vehicles. It is found that the equivalent fuel consumption is the most objective and informative, from the user's point of view, characterizing the use of electric vehicles compared to indicating the amount of energy (kWh) required to overcome 100 miles of travel. Using the proposed method, the equivalent fuel economy of these electric vehicles is calculated, the results are plotted against. It is established that for Ukraine, considering the cost of energy carriers, the use of electric vehicles is the most costeffective compared to other countries.

scholarly journals A NOVEL MULTIPHASE BIDIRECTIONAL FLY-BACK CONVERTER TOPOLOGY IS APPLIED TO INDUCTION MOTOR DRIVE

2013 ◽  
pp. 145-150
Author(s):  
M.RAMA MOHANA RAO ◽  
CH. RAMBABU
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Low Voltage ◽  
Fuel Efficiency ◽  
High Gain ◽  
Voltage Regulation ◽  
Modern World ◽  
Power Sources ◽  
Hybrid Electric

Hybrid Electric Vehicle (HEV) is an emerging technology in the modern world because of the fact that it mitigates environmental pollutions and at the same time increases fuel efficiency of the vehicles. Bi-directional Fly – back Converter controls electric drive of HEV of high power and enhances its performance which is the reflection of the fact that it can generate Constant voltages. For hybrid electric vehicles, the batteries and the drive dc link may be at different voltages. The batteries are at low voltage to obtain higher volumetric efficiencies, and the dc link is at higher voltage to have higher efficiency on the motor side. Therefore, a power interface between the batteries and the drive’s dc link is essential. This power interface should handle power flow from battery to motor, motor to battery, external gen-set to battery, and grid to battery. This paper proposes a multi-power-port topology which is capable of handling multiple power sources and still maintains simplicity and features like obtaining high gain, wide load variations, lower output-current ripple, and capability of parallel-battery energy due to the modular structure. The scheme incorporates a transformer winding technique which drastically reduces the leakage inductance of the coupled inductor. The development and testing of a bidirectional fly-back dc–dc converter for hybrid electric vehicle is described in this paper. Simple hysteresis voltage control is used for dc-link voltage regulation. The simulation results are presented, and modeling the circuit by using MATLAB/SIMULINK Platform.

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