Fuel economy and emission of hybrid electric bus

2011 ◽  
Author(s):  
L. Tengteng ◽  
Q. Kongjian ◽  
G. Junhua ◽  
Z. Chunlong
Keyword(s):  
Fuel Economy ◽  
Hybrid Electric Bus ◽  
Electric Bus ◽  
Hybrid Electric

Engine torque command handling for a series hybrid electric bus

2016 ◽  
Vol 231 (5) ◽  
pp. 638-652 ◽  
Author(s):  
Minjae Kim
Keyword(s):  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Energy Management Strategy ◽  
Engine Torque ◽  
Hybrid Electric Bus ◽  
Electric Bus ◽  
Parallel Hybrid ◽  
Generator Unit ◽  
Hybrid Electric

The series hybrid electric vehicle makes it easier to have fully independent controls for the engine–generator unit and for the traction motors; this is not feasible in parallel hybrid electric vehicles or series–parallel hybrid electric vehicles. The existing research does not consider this feature. Therefore, a novel control method called engine torque command handling is developed in this study and is added to the optimal energy management strategy, namely dynamic programming; this makes the most of the inertia of the engine–generator unit. The hidden fuel economy improvement factor, as demonstrated by the the difference between the command and the behaviour, can then be found. As a result, a considerable improvement in the fuel economy with straightforward but powerful concepts, such as modification of the engine operating points and the on–off period, is developed in the series hybrid electric bus. The simulation is evaluated by AMEsim–Simulink co-simulation with the well-known urban bus test profiles: the Manhattan cycle, the Braunschweig cycle and the Orange County cycle. The results show the significant potential for reduction in the energy consumption without changing the components or the structure of the vehicle system. This method can be applied to any type of vehicle that allows independent engine power generation without interruption.

scholarly journals The Development and Verification of a Novel ECMS of Hybrid Electric Bus

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jun Wang ◽  
Qing-nian Wang ◽  
Peng-yu Wang ◽  
Xiao-hua Zeng
Keyword(s):  
Real Time ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hardware In The Loop ◽  
Real Time Control ◽  
Hybrid Electric Bus ◽  
Time Control ◽  
Electric Bus ◽  
Hybrid Electric ◽  
Strategy Design

This paper presents the system modeling, control strategy design, and hardware-in-the-loop test for a series-parallel hybrid electric bus. First, the powertrain mathematical models and the system architecture were proposed. Then an adaptive ECMS is developed for the real-time control of a hybrid electric bus, which is investigated and verified in a hardware-in-the-loop simulation system. The ECMS through driving cycle recognition results in updating the equivalent charge and discharge coefficients and extracting optimized rules for real-time control. This method not only solves the problems of mode transition frequently and improves the fuel economy, but also simplifies the complexity of control strategy design and provides new design ideas for the energy management strategy and gear-shifting rules designed. Finally, the simulation results show that the proposed real-time A-ECMS can coordinate the overall hybrid electric powertrain to optimize fuel economy and sustain the battery SOC level.

0D-1D Coupling for an Integrated Fuel Economy Control Strategy for a Hybrid Electric Bus

2011 ◽  
Author(s):  
Laura Tribioli ◽  
Fabrizio Martini ◽  
Giovanni Pede ◽  
Carlo Villante
Keyword(s):  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Bus ◽  
Electric Bus ◽  
Hybrid Electric

Optimization of Hybrid Electric Bus Control Strategy with Hybrid Optimization Algorithm

2013 ◽  
Vol 341-342 ◽  
pp. 924-930
Author(s):  
Jian Ping Gao ◽  
Zhen Nan Liu ◽  
Zhi Jun Guo ◽  
Yue Hui Wei
Keyword(s):  
Optimization Algorithm ◽  
Fuel Economy ◽  
Control Strategy ◽  
Dynamic Performance ◽  
Hybrid Optimization ◽  
Hybrid Electric Bus ◽  
Hybrid Optimization Algorithm ◽  
Electric Bus ◽  
Hybrid Electric ◽  
Strategy Parameters

control strategy is one of the most decisive techniques in Hybrid Electric Bus (HEB) and directly influences the dynamic performance and fuel economy. For achieving the best fuel economy and keeping the battery for a long time, First, power analytic control strategy was built; then, the hybrid optimization algorithm (HOA) based on Multi-island genetic Algorithm (MIGA) and NLPQL was built by ISIGHT software. HOA is adopted in control strategy parameters of HEB optimization. The results show that the best result can be obtained in few iterative times by HOA, the calculation time was reduce by 12 hours, the fuel economy was improved by 12% and find the rules between control strategy parameters and fuel economy the balance of the battery state of charge (SOC).

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