System Integration for the Environmental Friendly Electric Vehicle

2014 ◽  
Vol 709 ◽  
pp. 300-303
Author(s):  
Kuang Shine Yang ◽  
Chih Ming Chang

This paper introduced a new power flow control strategy for a variable speed engine-generator based range-extended electric vehicle. The specific fuel consumption map of the internal combustion engine (ICE) has been obtained by off-line experiments to achieve optimal fuel efficiency. Finally, a typical range-extended electric vehicle is modeled and investigated such as acceleration traversing ramp, maximum speed, fuel consumption and emission are performed on the dynamic model of a range-extended electric vehicle. The energy consumption and cost were compared to tradition range-extended electric vehicle. Computer simulation results obtained, confirm the validity and performance of the proposed power flow control approach using for series hybrid electric vehicle.

2005 ◽  
Vol 38 (1) ◽  
pp. 218-223 ◽  
Author(s):  
Kasemsak Uthaichana ◽  
Sorin Bengea ◽  
Raymond DeCarlo

Author(s):  
Guillermo Becerra ◽  
Jose´ Luis Mendoza-Soto ◽  
Luis Alvarez-Icaza

In this paper a new strategy for controlling the power flow in hybrid electric vehicles is described. The strategy focuses in the planetary gear system where kinematic and dynamic constraints must be satisfied. The aim is to satisfy driver demands and to reduce fuel consumption. The resultant power flow control is continuous and uses the internal combustion engine with the maximum possible efficiency. The strategy is not optimal, although it is inspired by the solution to most optimization problems. The main advantages are that the computational cost is low, when compared to optimization based approaches, and that it is easy to tune. The strategy is tested with simulations using a mathematical model of a power train of a hybrid diesel-electric bus subjected to the power demands of representative urban area driving cycles. Simulation results indicate that the strategy achieves small speed tracking errors and attains good fuel consumption reduction levels.


A bidirectional chopper (BDC) is the one which can interface main source (HVS), auxiliary source (LVS) and a DCBus voltage at different levels which is implemented in Hybrid Electric Vehicle (HEV). This converter operation is of two modes namely dual source powering mode and energy re generation mode along with power flow control in both the directions. And also the independent power flow control across two sources (i.e. the dual source buck-boost mode). The operation, closed loop control of artificial neural network (ANN) and the comparison between PI and ANN control are provided in simulation results.


2016 ◽  
Vol 78 (6) ◽  
Author(s):  
Mohd Sabirin Rahmat ◽  
Fauzi Ahmad ◽  
Ahmad Kamal Mat Yamin ◽  
Noreffendy Tamaldin ◽  
Vimal Rau Aparow ◽  
...  

This paper provided a validated modeling and a simulation of a 6 degree freedom vehicle longitudinal model and drive-train component in a series hybrid electric vehicle. The 6-DOF vehicle dynamics model consisted of tire subsystems, permanent magnet synchronous motor which acted as the prime mover coupled with an automatic transmission, hydraulic brake subsystem, battery subsystem, alternator subsystem and internal combustion engine to supply the rotational input to the alternator. A speed and torque tracking control systems of the electric power train were developed to make sure that the power train was able to produce the desired throttle torque in accelerating the vehicle. A human-in-the-loop-simulation was utilized as a mechanism to evaluate the effectiveness of the proposed hybrid electric vehicle. The proposed simulation was used as the preliminary result in identifying the capability of the vehicle in terms of the maximum speed produced by the vehicle and the capability of the alternator to recharge the battery. Several tests had been done during the simulation, namely sudden acceleration, acceleration and braking test and unbounded motion. The results of the simulation showed that the proposed hybrid electric vehicle can produce a speed of up to 70 km/h with a reasonable charging rate to the battery. The findings from this study can be considered in terms of design, optimization and implementation in a real vehicle.


2021 ◽  
Author(s):  
Tabassum Haque ◽  
Tushar Kanti Roy ◽  
Farjana Faria ◽  
Most. Mahmuda Khatun ◽  
Tanmoy Sarkar ◽  
...  

2020 ◽  
Vol 13 (5) ◽  
pp. 953-960 ◽  
Author(s):  
Lucas Stefano de Souza Pelegrino ◽  
Marcelo Lobo Heldwein ◽  
Gierri Waltrich

Author(s):  
Guillermo Becerra ◽  
Luis Alvarez-Icaza ◽  
Alfonso Pantoja-Vázquez

Two control strategies for power flow control in hybrid electric vehicles (HEVs) with parallel configuration and a planetary gear system as a power coupling device between the internal combustion engine and the electric machine are proposed in this paper. The aim of both strategies is to determine, for a given driving cycle, an appropriate mixture of the power provided by the two engines. Performance is measured not only in terms of fuel consumption; driving cycle tracking and preservation of energy in the bank of batteries are also considered. The first strategy, named the PGS strategy as it is designed around the planetary gear system, is heuristic, inspired by bang–bang optimal control formulations and has low computational load, while the second is an optimal one derived from Pontryagin’s minimum principle (PMP). It is shown that, under appropriate choice of the weighting parameters in the Hamiltonian of the PMP, both strategies give very similar results and, therefore, that the PGS strategy corresponds to a feasible solution to an optimization problem. Both strategies can be implemented in real time, however, the PGS strategy is easier to tune. Tuning of the strategies’ parameters is independent of the driving cycle. The power flow control laws are continuous and enforce the use of the internal combustion engine with the maximum possible efficiency. The strategies are tested with simulations of a power train of a hybrid diesel–electric bus subjected to the demands of four representative urban area driving cycles. Although optimization solutions are based on simplified dynamic models, simulation results are verified with more detailed dynamic models of the HEV main subsystems. This allows us to evaluate the accuracy of the results and to verify the hypothesis established in the optimization formulation. Simulation results indicate that both strategies attain good fuel consumption reduction levels.


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