scholarly journals An Adaptive-Equivalent Consumption Minimum Strategy for an Extended-Range Electric Bus Based on Target Driving Cycle Generation

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1805 ◽  
Author(s):  
Hongwei Liu ◽  
Chantong Wang ◽  
Xin Zhao ◽  
Chong Guo
Keyword(s):  
Driving Cycle ◽  
Electric Bus ◽  
Extended Range

scholarly journals Stochastic Driving Cycle Synthesis for Analyzing the Energy Consumption of a Battery Electric Bus

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 55586-55598 ◽  
Author(s):  
Klaus Kivekas ◽  
Jari Vepsalainen ◽  
Kari Tammi
Keyword(s):  
Energy Consumption ◽  
Driving Cycle ◽  
Electric Bus

scholarly journals Development of Driving Cycle Construction for Hybrid Electric Bus: A Case Study in Zhengzhou, China

2020 ◽  
Vol 12 (17) ◽  
pp. 7188
Author(s):  
Jiankun Peng ◽  
Jiwan Jiang ◽  
Fan Ding ◽  
Huachun Tan
Keyword(s):  
Transfer Matrix ◽  
Electricity Consumption ◽  
Original Data ◽  
Performance Measure ◽  
Driving Cycle ◽  
Statistical Characteristics ◽  
Hybrid Electric Bus ◽  
Navigation Function ◽  
Electric Bus ◽  
Hybrid Electric

A driving cycle is important to accomplish an accurate depiction of a vehicle’s driving characteristics as the traction motor’s flexible response to stop and start commands. In this paper, the driving cycle construction of an urban hybrid electric bus (HEB) in Zhengzhou, China is developed in which a measurement system integrating global positioning and inertial navigation function is used to acquire driving data. The collected data are then divided into acceleration, deceleration, uniform, and stop fragments. Meanwhile, the velocity fragments are classified into seven state clusters according to their average velocities. A transfer matrix applied to reveal the transfer relationship of velocity clusters can be obtained with statistical analysis. In the third stage, a three-part construction method of driving cycle is designed. Firstly, according to the theory of Markov chain, all the alternative parts that satisfy the construction’s precondition are selected based on the transfer matrix and Monte Carlo method. The Zhengzhou urban driving cycle (ZZUDC) could be determined by comparing the performance measure (PM) values subsequently. Eventually, the method and the cycle are validated by the high correlation coefficient (0.9972) with original data of ZZUDC than that of the other driving cycle (0.9746) constructed with traditional micro-trip and as well by comparing several statistical characteristics of ZZUDC and seven international cycles. Particularly, with around 20.5 L/100 km fuel and approximately 12.8 kwh/100 km electricity consumption, there is a narrow gap between the energy consumption of ZZUDC and WVUCITY, and their characteristics are similar.

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.

Study on Powertrain Matching Based on Driving Cycle for Hybrid Electric Vehicle

2013 ◽  
Vol 288 ◽  
pp. 175-182 ◽  
Author(s):  
Xi Ming Wang ◽  
Hong Wen He ◽  
Heng Lu Tang ◽  
Hong Zhou Qin ◽  
Jian Kun Peng
Keyword(s):  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Emissions Reduction ◽  
Power Performance ◽  
Matching Method ◽  
Hybrid Powertrain ◽  
Electric Bus ◽  
Hybrid Electric ◽  
Kinetic Equilibrium

The performance of fuel economy and emissions reduction of hybrid electric vehicles (HEVs) strongly depends on the powertrains’ matching and its energy control strategy. The theoretic matching method only based on the theoretical equation of kinetic equilibrium, which is a traditional method, could not take fully use of the advantages of HEV under a certain driving cycle because it doesn’t consider the target driving cycle. In order to match the hybrid powertrain that operates more efficiently under the target driving cycle, the matching method based on driving cycle is presented. The powertrain of a hybrid electric bus is matched, modeled and simulated on the CRUISE, a forwards simulation platform from AVL. The simulation results show that the matching method based on driving cycle presented in this paper could not only meet the requirements of the power performance, but also operate efficiently under the target driving cycle.

scholarly journals Dynamic Programming-Based Energy Management System for Range-Extended Electric Bus

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaogang Wu ◽  
Jingfu Chen ◽  
Chen Hu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Management ◽  
Driving Cycle ◽  
Flow Diagram ◽  
Optimal Control Strategy ◽  
Diagram Method ◽  
Powertrain System ◽  
Electric Bus ◽  
Urban Bus

The heavy computational burden associated with the application of the traditional DP strategy to the energy management of range-extended electric buses poses a serious problem. On the basis of one Chinese typical urban bus driving cycle, an optimal control strategy is designed according to the SOC consumption trend, which is optimized by the DP algorithm. The dissipative energy and the energy-traction efficiency are our evaluation indices. The energy efficiencies of the powertrain system and components are analyzed by the energy flow diagram method. The results show that when the range-extended electric bus runs 35 Chinese typical urban bus driving cycles, the energy consumption and the energy efficiency of the powertrain system, which are optimized by the traditional DP strategy, can reach 2844.28 MJ and 31.29%, respectively. Compared with the traditional bus, the energy consumption can be reduced by 31.08%. The energy consumption and the energy efficiency of the powertrain system, which are based on one driving cycle optimal strategy, can reach 2857.69 MJ and 31.14%, respectively. The energy consumption is 0.47% higher than that with the traditional DP strategy, but the computation time is reduced by 96.85%.

Dynamic Performance Analysis of Extended Range/Plug-In Electric Bus

2015 ◽  
Vol 713-715 ◽  
pp. 1351-1355
Author(s):  
Hong Wei Chen ◽  
Xin Zhang ◽  
Xiao Shuai Zhang
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Dynamic Performance ◽  
City Bus ◽  
Limit Value ◽  
Powertrain System ◽  
Electric Bus ◽  
Extended Range ◽  
New Type ◽  
Dynamic Performance Analysis

A new type powertrain system architecture for city electric bus was introduced, which combines the function of Extended-Range Electric Vehicle (E-REV) and Plug-in Hybrid Electric Vehicle (P-HEV). Five driving modes were designed and its dynamics were analyzed. Numerical method on dynamics was proposed. The dynamic performance parameter of five drive modes were calculated and analyzed. The results indicate that the dynamic performance reaches the limit value at full drive mode and meet the requirement of city bus.

Research of Driving Cycle for Electric Bus of Expo Guozhan Line

2013 ◽  
Vol 340 ◽  
pp. 163-167
Author(s):  
Pan Gao ◽  
Xi Chan Zhu ◽  
Zhi Xiong Ma ◽  
Shun Liang Zhu
Keyword(s):  
Research And Development ◽  
Driving Cycle ◽  
Huge Data ◽  
Electric Bus ◽  
The Difference

Based on huge data got during the EXPO period, this paper researched the running character of the buses run on EXPO Guozhan line and constructed the driving cycle. According to statistical principle, defined thirty six characteristics and chosen twenty three characteristics of them as index characteristics. In this paper we constructed the driving cycle by ways of the difference at index characteristics. When the difference between the totality and the temporary cycle is within 10%, the temporary cycle could be received as the driving cycle of the totality. The research gave the driving cycle of the bus line running in China. In the following research and development of the electric bus, Researchers could use this driving cycle to helping develop, test and verify the electric bus.

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