Influence of Driving Cycle Uncertainty on Electric City Bus Energy Consumption

This paper proposes a reformed dynamic programming (DP) based energy management strategy for a city bus driven by dual-motor coupling propulsion system(DMCPS). An instantaneous optimal problem of DMCPS’s total energy loss is constructed to solve the torque allocation between two motors. Taking the results as extra constraints, a reformed DP architecture aimed at optimal energy consumption is established, where the state variables are the battery’s SOC and operating modes of DMCPS, with a sole decision variable of mode switching action. The optimization results show a close performance to the original method, with the calculation efficiency greatly improved and the calculation time reduced by nearly 97%. To obtain practical rules for real-time application, the mode switching schedule is extracted based on a RBF-SVM classifier, and the torque allocation is ruled by linear function. Simulation results demonstrate that the extracted rules can be executed through an on-board processor, with energy consumption reduced by 2.19% compared to the original rule-based strategy.

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Simplified Model of City Bus Dynamics as a Tool of an Energy Consumption Estimation

Springer Proceedings in Mathematics & Statistics - Dynamical Systems: Modelling ◽

10.1007/978-3-319-42402-6_26 ◽

2016 ◽

pp. 327-339 ◽

Cited By ~ 1

Author(s):

Tomasz Pałczyński

Keyword(s):

Energy Consumption ◽

Simplified Model ◽

City Bus

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Annual Variation in Energy Consumption of an Electric Vehicle Used for Commuting

Energies ◽

10.3390/en13184639 ◽

2020 ◽

Vol 13 (18) ◽

pp. 4639 ◽

Cited By ~ 1

Author(s):

Anatole Desreveaux ◽

Alain Bouscayrol ◽

Elodie Castex ◽

Rochdi Trigui ◽

Eric Hittinger ◽

...

Keyword(s):

Energy Consumption ◽

Electric Vehicle ◽

Experimental Measurement ◽

Air Conditioning ◽

Annual Variation ◽

Accurate Determination ◽

Driving Cycle ◽

Simulation Tool ◽

Real Vehicle

The energy consumption of an electric vehicle is primarily due to the traction subsystem and the comfort subsystem. For a regular trip, the traction energy can be relatively constant but the comfort energy has variation depending on seasonal temperatures. In order to plan the annual charging operation of an eco-campus, a simulation tool is developed for an accurate determination of the consumption of an electric vehicle throughout year. The developed model has been validated by comparison with experimental measurement of a real vehicle on a real driving cycle. Different commuting trips are analyzed over a complete year. For the considered city in France (Lille), the comfort energy consumption has an overconsumption up to 33% in winter due to heating, and only 15% in summer due to air conditioning. The urban commuting driving cycle is more affected by the comfort subsystem than extra-urban trips.

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Research on the NOx Emission and Exhaust Gas Temperature Characteristics of City Bus under the City Driving Cycle

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.864-867.1648 ◽

2013 ◽

Vol 864-867 ◽

pp. 1648-1653

Author(s):

Chang Yuan Wang ◽

Kong Jian Qin ◽

Jun Hua Gao

Keyword(s):

High Speed ◽

Emission Rate ◽

Driving Cycle ◽

Nox Emission ◽

Emission Measurement ◽

Vehicle Speed ◽

Gas Temperature ◽

Instantaneous Rate ◽

Low Speed ◽

City Bus

Using portable emission measurement system, an experimental study on the NOx emission characteristics of city bus in practical operation are conducted, the eigenvalue of driving cycle are analyzed by short trip method. The results show that: idling time accounted for 20.392%, ratio of acceleration which between -0.5 m/s2 and 0.5 m/s2 accounted for as high as 83.314%.NOx emissions are greatly affected by the speed of vehicle: the instantaneous rate and total amount of NOx emission under high speed are much higher than low speed, the average urea injection under high speed is 3.5 times than low speed. When the vehicle speed is between 20-25km/h, the average emission rate of NOx is about 0.074g/s，while the time proportion of urea injection is under 40%;while the vehicle speed is above 55km/h, the average emission rate of NOx is about 0.025g/s，while the time proportion of urea injection can reach as high as 80%.

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Review on Construction Procedures of Driving Cycles

International Journal of Engineering and Management Sciences ◽

10.21791/ijems.2020.2.31. ◽

2020 ◽

Vol 5 (2) ◽

pp. 266-285

Author(s):

Levente Czégé ◽

Attila Vámosi ◽

Imre Kocsis

Keyword(s):

Energy Consumption ◽

Data Collection ◽

Dynamic Simulation ◽

Statistical Evaluation ◽

Driving Cycle ◽

Driving Cycles ◽

Construction Techniques ◽

The Future ◽

Evaluation Of Data

The goal of this paper is to give an overview of the literature of construction techniques of driving cycles. Our motivation for the overview is the future goal of constructing our own driving cycles for various types of vehicles and routes. This activity is part of a larger project focusing on determination of fuel and energy consumption by dynamic simulation of vehicles. Accordingly, the papers dealing with sample route determination, data collection and processing, driving cycle construction procedures, statistical evaluation of data are in our focus.

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An Innovative Design of Decoupled Regenerative Braking System for Electric City Bus Based on Chinese Typical Urban Driving Cycle

Mathematical Problems in Engineering ◽

10.1155/2020/8149383 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Yanfeng Xiong ◽

Qiang Yu ◽

Shengyu Yan ◽

Xiaodong Liu

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Control Strategy ◽

Recovery Rate ◽

Energy Recovery ◽

Regenerative Braking ◽

City Bus ◽

Braking System ◽

Recovery System ◽

Braking Energy Recovery

This paper proposes a novel decoupled approach of a regenerative braking system for an electric city bus, aiming at improving the utilization of the kinetic energy for rear axle during a braking process. Three contributions are added to distinguish from the previous research. Firstly, an energy-flow model of the electric bus is established to identify the characteristic parameters which affect the energy-saving efficiency of the vehicle, while the key parameters (e.g., driving cycles and the recovery rate of braking energy) are also analyzed. Secondly, a decoupled braking energy recovery scheme together with the control strategy is developed based on the characteristics of the power assistance for electric city bus which equips an air braking system, as well as the regulatory requirements of ECE R13. At last, the energy consumption of the electric city bus is analyzed by both the simulation and vehicle tests, when the superimposed and the decoupled regenerative braking system are, respectively, employed for the vehicle. The simulation and actual road test results show that compared with the superposition braking system of the basic vehicle, the decoupled braking energy recovery system after the reform can improve the braking energy recovery rate and vehicle energy-saving degree. The decoupled energy recovery system scheme and control strategy proposed in this paper can be adopted by bus factories to reduce the energy consumption of pure-electric buses.

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A strategy of electrical energy management for internal combustion engine vehicle based on driving cycle recognition and electrical load perception

Advances in Mechanical Engineering ◽

10.1177/1687814018809236 ◽

2018 ◽

Vol 10 (11) ◽

pp. 168781401880923

Author(s):

Yuefei Wang ◽

Nan Zhang ◽

Ye Wu ◽

Baijun Liu ◽

Yuan Wu

Keyword(s):

Energy Consumption ◽

Energy Management ◽

Fuel Economy ◽

Time Window ◽

Combustion Engine ◽

Electrical Energy ◽

Driving Cycle ◽

Electrical Load ◽

Internal Combustion Engine Vehicle ◽

Load Perception

Electrical energy consumption is an important component of energy consumption for internal combustion engine vehicle, which directly affects the fuel economy. A bus-based electrical energy management system is built, and an electrical energy management strategy based on driving cycle recognition and electrical load perception is presented to achieve the refined management of vehicle energy. Six typical driving cycles are selected to establish an improved learning vector quantization neural network model for driving cycle recognition. The corresponding model training algorithm is designed by utilizing a similar driving cycle classification and the gradient optimization so that the better recognition accuracy and the less computation intensity can be obtained. An online recognition mechanism based on sliding time window is devised, and the optimal time window length is determined. To minimize fuel consumption, a dynamic optimal regulation strategy for the output power of the alternator and battery, which considers driving cycle recognition and electrical load perception, is proposed. Experimental results show that the strategy can effectually improve the vehicle fuel economy according to the driving cycle and the electrical load change and decrease the fuel consumption per 100 miles of vehicle.

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