Impacts of Diverse Driving Cycles on Electric and Hybrid Electric Vehicle Performance

1997 ◽  
Author(s):  
Feng An ◽  
Matthew Barth ◽  
George Scora
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Vehicle Performance ◽  
Driving Cycles ◽  
Hybrid Electric

scholarly journals Research on energy management strategy considering battery life for plug-in hybrid electric vehicle

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879776 ◽  
Author(s):  
Jianjun Hu ◽  
Zhihua Hu ◽  
Xiyuan Niu ◽  
Qin Bai
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Battery Life ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Comprehensive Test ◽  
Hybrid Electric

To improve the fuel efficiency and battery life-span of plug-in hybrid electric vehicle, the energy management strategy considering battery life decay is proposed. This strategy is optimized by genetic algorithm, aiming to reduce the fuel consumption and battery life decay of plug-in hybrid electric vehicle. Besides, to acquire better drive-cycle adaptability, driving patterns are recognized with probabilistic neural network. The standard driving cycles are divided into urban congestion cycle, highway cycle, and urban suburban cycle; the optimized energy management strategies in three representative driving cycles are established; meanwhile, a comprehensive test driving cycle is constructed to verify the proposed strategies. The results show that adopting the optimized control strategies, fuel consumption, and battery’s life decay drop by 1.9% and 3.2%, respectively. While using the drive-cycle recognition, the features of different driving cycles can be identified, and based on it, the vehicle can choose appropriate control strategy in different driving conditions. In the comprehensive test driving cycle, after recognizing driving cycles, fuel consumption and battery’s life decay drop by 8.6% and 0.3%, respectively.

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.

scholarly journals Multiobjective optimisation of a series hybrid electric vehicle using DIRECT algorithm

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Abdelmoula Rihab ◽  
◽  
Ben Hadj Naourez ◽  
Chaieb Mohamed ◽  
Neji Rafik ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Vehicle Performance ◽  
Performance Requirements ◽  
Toxic Emissions ◽  
Series Hybrid Electric Vehicle ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

With the economic development, transportation in the city becomes more crowded. Furthermore, fuel consumption is causing a serious problem of pollution in the urban environment. Hybrid electric vehicles are considered as a good solution compared to conventional internal combustion engine vehicles. In order to solve those problems, the components parameters of a series hybrid electric vehicle are selected and tested with the ADvanced VehIcle SimulatOR (ADVISOR) simulation tool, which is a software-based on Matlab_simulink. Then, an optimisation was done to minimise simultaneous fuel consumption and emissions (HC, CO, and NOx) of the vehicle engine. In addition, the driving performance requirements are also examined during the urban dynamometer driving schedule (UDDS) to fix their optimal control parameters. Finally, the results show that those steps help reduce fuel consumption and emissions while guaranteeing vehicle performance. Hence, the series hybrid electric vehicle greatly improves fuel economy and reduces toxic emissions.

Regenerative Braking Potential and Energy Simulations for a Plug-In Hybrid Electric Vehicle Under Real Driving Conditions

2009 ◽  
Author(s):  
L. A. S. B. Martins ◽  
J. M. O. Brito ◽  
A. M. D. Rocha ◽  
J. J. G. Martins
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Regenerative Braking ◽  
Driving Cycles ◽  
Energy Flows ◽  
Hybrid Electric ◽  
Series Type ◽  
Energy Simulations ◽  
Electric Traction

There are several possible configurations and technologies for the powertrains of electric and hybrid vehicles, but most of them will include advanced energy storage systems comprising batteries and ultra-capacitors. Thus, it will be of capital importance to evaluate the power and energy involved in braking and the fraction that has the possibility of being regenerated. The Series type Plug-in Hybrid Electric Vehicle (S-PHEV), with electric traction and a small Internal Combustion Engine ICE) powering a generator, is likely to become a configuration winner. The first part of this work describes the model used for the quantification of the energy flows of a vehicle, following a particular route. Normalised driving-cycles used in Europe and USA and real routes and traffic conditions were tested. The results show that, in severe urban driving-cycles, the braking energy can represent more than 70% of the required useful motor-energy. This figure is reduced to 40% in suburban routes and to a much lower 18% on motorway conditions. The second part of the work consists on the integration of the main energy components of an S-PHEV into the mathematical model. Their performance and capacity characteristics are described and some simulation results presented. In the case of suburban driving, 90% of the electrical motor-energy is supplied by the battery and ultra-capacitors and 10% by the auxiliary ICE generator, while on motorway these we got 65% and 35%, respectively. The simulations also indicate an electric consumption of 120 W.h/km for a small 1 ton car on a suburban route. This value increases by 11% in the absence of ultra-capacitors and a further 28% without regenerative braking.

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.

Optimization Study of CVT Speed Ratio to Plug-In Hybrid Electric Vehicle

2014 ◽  
Vol 986-987 ◽  
pp. 1094-1097
Author(s):  
Min Zhou ◽  
Yan Fang Zhang
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Speed Ratio ◽  
Target Speed ◽  
Driving Cycles ◽  
Motor Efficiency ◽  
Optimization Study ◽  
Reverse Optimization ◽  
Energy Economy ◽  
Hybrid Electric

Taking CVT plug-in hybrid electric vehicle as the study subject, the objective function of the energy economy is created. In view of engine, motor efficiency and CVT efficiency coupled relationship; proposed reverse optimization algorithm to solve function. The target speed ratio of optimal energy economy is obtained in different SOC (State Of Charge), velocity, acceleration and slope. On the Matlab/Simulink platform, the system simulation model is built and simulated. The results shows that the target speed ration optimized control law in the case of no additional hardware cost , energy economy save about respectively 3.6% ,4.6%,6.7% in driving cycles of the NEDC,UDDS,HWFET before optimization.

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