The novel application of optimization and charge blended energy management control for component downsizing within a plug-in hybrid electric vehicle

The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialization. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Contained within this paper is an optimization study in which a charge blended strategy is used to facilitate the downsizing of the electrical machine, the internal combustion engine and the high voltage battery. An improved Equivalent Consumption Method has been used to manage the optimal power split within the powertrain as the PHEV traverses a range of different drivecycles. For a target CO2 value and drivecycle, results show that this approach can yield significant downsizing opportunities, with cost reductions on the order of 2%–9% being realizable

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

An optimization and analysis framework for TCO minimization of plug-in hybrid heavy-duty electric vehicles

This paper develops an optimization framework to minimize the Total Cost of Ownership (TCO) for Plug-in Hybrid Electric Vehicles (PHEVs). In this paper, TCO is the summation of operational and main vehicle powertrain components cost. The developed optimization framework is formulated via combining convex optimization and Dynamic Programming technique. This framework aims at minimizing TCO by optimizing not only the sizing of the main powertrain components but also the powertrain topology. Using the developed optimization framework, this paper elaborates relevant design factors for a considered bus application namely: i) the value of equipping a HEV with plug-in functionality; ii) the effect of battery aging and replacement cost; iii) the sensitivity to fuel and electricity cost; Simulation results show that the TCO can be reduced by having plug-in functionality in the HEVs. However, this may not hold if the electricity price (in Euros/kWh) is higher than certain times of the fuel price (in Euros/kWh), e.g. 2.25 for the simulated cases in this paper. Simulation results also suggest that it is more profitable to equip the vehicle with a big enough battery to avoid replacing it during the vehicle economical life

Quality of Service and Associated Communication Infrastructure for Electric Vehicles †

Transportation electrification is pivotal for achieving energy security and emission reduction goals. Electric vehicles (EVs) are at the forefront of this transition, driving the development of new EV technologies and infrastructure. As this trend gains momentum, it becomes essential to enhance the quality of service (QoS) of EVs to encourage their widespread adoption. This paper has been structured with two primary aims to effectively address the above timely technological needs. Firstly, it comprehensively reviews the various QoS factors that influence EVs’ performance and the user experience. Delving into these factors provides valuable insights into how the QoS can be improved, thereby fostering the increased use of EVs on our roads. In addition to the QoS, this paper also explores recent advancements in communication technologies vital for facilitating in-formation exchanges between EVs and charging stations. Efficient communication systems are crucial for optimizing EV operations and enhancing user experiences. This paper presents expert-level technical details in an easily understandable manner, making it a valuable resource for researchers dedicated to improving the QoS of EV communication systems, who are tirelessly working towards a cleaner, more efficient future in transportation. It consolidates the current knowledge in the field and presents the latest discoveries and developments, offering practical insights for enhancing the QoS in electric transportation. A QoS parameter reference map, a detailed classification of QoS parameters, and a classification of EV communication technology references are some of the key contributions of this review paper. In doing so, this paper contributes to the broader objectives of promoting transportation electrification, enhancing energy security, and reducing emissions

Towards Wind Energy-based Charging Stations: A Review of Optimization Methods

Due to the growing importance of renewable sources in sustainable energy systems, the strategic deployment of robust optimization techniques plays a crucial role in the design of Electric Vehicle Charging Stations (EVCSs). These stations need to smoothly incorporate renewable sources, ensuring optimal energy utilization. This study provides a comprehensive overview of the methodologies and approaches employed in the enhancement of wind energy based EVCSs. The aim is to discern the most efficacious techniques for optimizing charging stations. Researchers engage diverse strategies and methodologies in the realm of sizing and optimization, encompassing a spectrum of algorithmic implementations and software solutions. Evidently, each algorithm or software application bears distinctive merits and demerits. Singular reliance on a solitary algorithm or software for charging utility optimization is discerned to be potentially limiting. The investigation reveals that achieving better results in Electric Vehicle Charging Station (EVCS) optimization is facilitated by the collaborative use of multiple algorithms like GA, PSO, and ACO, among others, or software tools like Homer or RETScreen

Electromobility Studies Based on Convex Optimization DESIGN AND CONTROL ISSUES REGARDING VEHICLE ELECTRIFICATION

This article presents a framework to study design tradeoffs in the search for electromobility solutions based on approximate modeling of the power flows in the powertrain as a function of component sizes. An important consequence of the modeling assumptions is that the optimal energy management and component sizes can be computed simultaneously in a convex program, which means that competing designs can be evaluated in an objective way, avoiding the influence of a separate control system design. The fact that the optimization problem is convex allows large problems to be solved with moderate computational resources, which can be exploited by, for example, running optimizations over very long driving cycles. The problem formulation also admits design decisions for the charging infrastructure to be included in the optimization

Operational Cost Minimization of Grid Connected Microgrid System Using Fire Fly Technique

oai:oai.jieee.a2zjournals.com:article/1Present time, green energy sources interfacing to the utility grid by utilizing microgrid system is very vital to satisfy the ever increasing energy demand. Optimal operation of the microgrid system improved the generation from the distributed renewable energy sources at the lowest operational cost. Large amount of constraints and variables are associated with the microgrid economic operation problem. Thus, this problem is very complex and required efficient technique for handing the problem adequately. This research utilized the fire fly optimization technique for solving the formulated microgrid operation problem. Fire fly algorithm is based on the behaviour and nature of the fire flies. A microgrid system modelling which incorporated various distributed energy sources such as solar photo voltaic, wind turbine, micro tur-bine, fuel cell, diesel generator, electric vehicle technology, etc.. Energy storage system is utilized in this research for supporting renewable energy sources’ integration in more reliable and qualitative way. Further, the electric vehicle technology i.e. battery electric vehicle, plug-in hybrid electric vehicle and fuel cell electric vehicle are utilized to support the microgrid and utility grid systems with respect to variable demands. Optimal operational cost-minimization problem of the developed microgrid system is solved by fire fly algorithm and compared with the grey wolf opti-mization and particle swarm optimization techniques. By comparative analysis it is clear that the fire fly algorithm provides the minimum operational cost of microgrid system as compared to the GWO and PSO. MATLAB software is utilized to model the microgrid system and implementation of the optimization techniques