Application of Cuk converter together with battery technologies on the low voltage DC supply for electric vehicles

2015 ◽  
Author(s):  
Wenzheng Xu ◽  
K.W.E. Cheng ◽  
K.W. Chan
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Cuk Converter

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

New energy bound-based model for optimal charging of electric vehicles with solar photovoltaic considering low-voltage network's constraints

2021 ◽  
Vol 129 ◽  
pp. 106862
Author(s):  
Andrés Felipe Cortés Borray ◽  
Alejandro Garcés ◽  
Julia Merino ◽  
Esther Torres ◽  
Javier Mazón
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Solar Photovoltaic ◽  
New Energy ◽  
Energy Bound

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

Low-voltage-battery powered hybrid-GaN/SiC Y-Inverter dual-rotor Halbach motor drive for light electric vehicles

2021 ◽  
Author(s):  
Hai N. Tran ◽  
Alberto Castellazzi ◽  
Shinichi Domae ◽  
Tenghui Dong ◽  
Taketsune Nakamura
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Motor Drive

Electric vehicles and power quality in low voltage networks: Real data analysis and modeling

2022 ◽  
Vol 305 ◽  
pp. 117718
Author(s):  
S. Torres ◽  
I. Durán ◽  
A. Marulanda ◽  
A. Pavas ◽  
J. Quirós-Tortós
Keyword(s):  
Data Analysis ◽  
Power Quality ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Real Data ◽  
Real Data Analysis

scholarly journals Implementation and Experimental Verification of Smart Junction Box for Low-Voltage Automotive Electronics in Electric Vehicles

2020 ◽  
Vol 10 (7) ◽  
pp. 2214
Author(s):  
Sang Wook Lee ◽  
Soo-Whang Baek
Keyword(s):  
Electric Vehicles ◽  
Printed Circuit Board ◽  
Pulse Width Modulation ◽  
Low Voltage ◽  
Short Circuit ◽  
Circuit Board ◽  
Area Network ◽  
Automotive Electronics ◽  
Overload Protection ◽  
The Impact

In this study, we designed and implemented a smart junction box (SJB) that was optimized for supplying power to low-voltage headlights (13.5 V) in electric vehicles. The design incorporated a number of automotive semiconductor devices, and components were placed in a high-density arrangement to reduce the overall size of the final design. The heat generated by the SJB was efficiently managed to mount an Intelligent Power Switch (IPS), which was used to power the headlights onto the printed circuit board (PCB) to minimize the impact on other components. The SJB was designed to provide power to the headlights via pulse width modulation to extend their lifetime. In addition, overload protection and fail/safe functions were implemented in the software to improve the stability of the system, and a controller area network (CAN) bus was provided for communications with various components in the SJB as well as with external controllers. The performance of the SJB was validated via a load operation test to assess the short circuit and overload protection functions, and the output duty cycle was evaluated across a range of input voltages to ensure proper operation. Based on our results, the power supplied to the headlights was found to be uniform and stable.

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