Multi-objective component sizing of plug-in hybrid electric vehicle for optimal energy management

Rashid

2020

IJEECS

<p>The significance of power or energy measurement has been very acute in recent times with the increase of Grid-Tied Solar PV system that needs Net-Metering. Power can be flown in both directions, from grid to load or from load (PV- Panel) to grid line. If power flow from both side is not calculated and surplus power which is not being used at the time instant is not stored, accurate billing is not possible. That is why a bidirectional power meter is required which can measure both the positive and negative power at any instant. The aim of this paper is to develop a bidirectional power meter using microcontroller. The work of this paper constitutes a microcontroller, a current sensor, bulbs as load and a display. The rms values of voltage and current is determined and showed in the display. Then the calibration is done inside the developed program. After that the power is calculated and showed in the display. Then the direction of the power is determined depending on the direction (whether positive or negative) of the power which is also dependent on the phase difference between the voltage and current. If there is no phase difference between the voltage and current, then the power is positive and leaving from the grid. If there is 180 degree phase difference between the voltage and current, then the power is negative and entering to the grid. The direction of the power flow is very important for efficiently of the proposed meter. For some defined load the accuracy of the developed meter is calculated as 94%.</p>

Section: Negative Powermentioning

confidence: 99%

Design and development of Bi directional power meter using microcontroller

Rashid

2020

IJEECS

International Journal of Agricultural and Biological Engineering

“…As the parameter optimization design is a multi-objective optimization problem, the weighted combination method is used to transfer multi-objective functions into a single objective function [25] . The expression is:…”

Section: Transformation Of Optimization Objective Functionmentioning

confidence: 99%

“…According to Section 4.3, the powertrain ratio relationship constraints include Equations (21), (23), (24) and (25).…”

Section: Powertrain Ratio Relationship Constraintsmentioning

confidence: 99%

See 1 more Smart Citation

Powertrain parameter matching and optimal design of dual-motor driven electric tractor

Xie

Mao

2019

The rationality of powertrain parameter design has a significant influence on the traction performance and economic performance of electric tractor. At present, researches on powertrain parameter design mainly focus on electric vehicles, and electric agricultural machinery draw much less attention. Therefore, a method of powertrain parameter matching and optimization design for electric tractor was proposed in this paper, which was based on dual-motor coupling drive mode. The particle swarm optimization (PSO) algorithm based on mixed penalty function was used for parameter optimization. Parameter optimization design was programmed using MATLAB. A simulation dynamic model with optimization design variables of electric tractor powertrain was established based on MATLAB/Simulink. Compared with the simulation results before optimization, the objective functions were optimized and the traction performance of electric tractor was improved, which indicated the effectiveness of the proposed method.

“…The undercharged cell is responsible to reduce the efficiency while overcharged cells can sabotage the storage. Therefore, charge equalization among the cells is vital to increase the battery performance and safety [5]. The proposed algorithm contributes to the equalization technique till all the cells getting equalized accordingly.…”

Section: Introductionmentioning

confidence: 99%

Charging and Discharging Control of Li-Ion Battery Energy Management for Electric Vehicle Application

Verasamy¹,

Faisal²,

Ker³

et al. 2018

IJET

Electric vehicle (EV) is now replacing the conventional fuel driven vehicle as it has strong contribution to face the challenges of global warming issues. This system has the energy storage device which can be introduced by lithium-ion (li-ion) battery banks. Lithium-ion is mostly popular because of its high capacity and efficiency. Nevertheless, li-ion battery needs protective mechanism to control overcharged or undercharged of the cell that can reduce the life expectancy and efficiency. Hence, a control model needs to develop to enhance the protection of battery. Therefore, the key issue of the research is to investigate the performance of Li-ion battery energy management system (BMS) for electrical vehicle applications by monitoring and balancing the cell voltage level of battery banks using Simulink software. A bidirectional flyback DC-DC converter is investigated in the BMS model to control the undercharging or overcharging of cells. An intelligent charge control algorithm is used for this purpose. Backtracking search optimization algorithm (BSA) is implemented to optimize the parameters for generating regulated PWM signal. Obtained results were observed within the safety operating range of Li-ion battery (3.73 V – 3.87V).