Hyperheuristics Trajectory Based Optimization for Energy Management Strategy (EMS) of Split Plug-In Hybrid Electric Vehicle (original) (raw)

A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

International Journal of Vehicular Technology, 2014

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a read...

A comprehensive review on energy management strategies of hybrid energy storage system for electric vehicles

International Journal of Energy Research, 2017

The attention on green and clean technology innovations is highly demanded of a modern era. Transportation has seen a high rate of growth in today's cities. The conventional internal combustion engine-operated vehicle liberates gasses like carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons, and water, which result in the increased surface temperature of the earth. One of the optimum solutions to overcome fossil fuel degrading and global warming is electric vehicle. The challenging aspect in electric vehicle is its energy storage system. Many of the researchers mainly concentrate on the field of storage device cost reduction, its age increment, and energy densities' improvement. This paper explores an overview of an electric propulsion system composed of energy storage devices, power electronic converters, and electronic control unit. The battery with high-energy density and ultracapacitor with high-power density combination paves a way to overcome the challenges in energy storage system. This study aims at highlighting the various hybrid energy storage system configurations such as parallel passive, active, battery-UC, and UC-battery topologies. Finally, energy management control strategies, which are categorized in global optimization, are reviewed.

Development and Evaluation of Intelligent Energy Management Strategy for Plug-in Hybrid Electric Vehicle

Transportation Research Board 92nd Annual MeetingTransportation Research Board, 2013

There has been significant interest in plug-in hybrid electric vehicles (PHEVs) as a means to decrease dependence on imported oil and to reduce greenhouse gases as well as other pollutant emissions. One of the critical considerations in PHEV development is the design of its energy-management strategy, which determines how energy in a hybrid powertrain should be produced and utilized as a function of various vehicle parameters. In this paper, we propose an intelligent energy-management strategy for PHEVs. At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic conditions on the travel route from intelligent transportation system technologies in generating a synthesized velocity trajectory for the trip. The synthesized velocity trajectory is then used to determine battery's charge-depleting control that is formulated as a mixed-integer linear programming problem to minimize the total trip fuel consumption. The strategy can be extended to optimize vehicle fuel consumption at the tour level if a preplanned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops along the tour are available. The effectiveness of the proposed strategy, both for the trip-and tour-based controls, was evaluated against the existing binary-mode energy-management strategy using real-world trip/tour examples in southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary-mode strategy are around 10%-15%.

A sub-optimal energy management strategy for hybrid electric vehicles

2008

The research activity performed in this dissertation focussed on the development of enhanced solutions for the architectures and the relative control of hybrid or conventional vehicles' power buses, with the aim to minimize the fuel consumption and the pollutant emissions. These goals would have to be obtained either improving the efficiency of every components in the vehicle or adopting a suitable energy management strategy, able to operate the "vehicle" system at its maximum global efficiency, while ensuring the fulfillment of the performances required from the driver, leaving unaffected the drivability of the vehicle and the on-board electrical loads supplies, as much as possible leaving the battery SOC at a costant level. Two research activity lines have been followed: the first one concerns a comparative analysis of the power bus architectures in vehicles with conventional or hybrid propulsion, for the detection of innovative solutions with high quality-of-electricservice and reliability performances, able to satisfy specific requests. The second activity involves the development and implementation of an algorithm for the management and control of the power bus in conventional and hybrid propulsion vehicles. Employing some acquired methodologies, the first research activity has led to the modeling of automotive components (power supply system, electro-mechanical drives and electrical loads) of the vehicle power system, the detection of critical drive cycles and critical loads activation sequences, the simulation of the power bus Abstract 2 architecture for the analysis in steady-state and transient conditions, with the purpose to realize a comparative evaluation among several existing or innovative power bus architectures. The comparative evaluation among different architectures has been made achievable with the design of the software so-called Evaluator, implemented in MATLAB environment: starting from the value of several performance indexes such as volume, weight, cost, reliability of the individual components and of whole system, quality of the bus voltage, Evaluator provides a global index that defines the adaptability of the evaluated architecture to a fixed application. The second research activity includes the energetic modelling of the propulsor and electric generation/storage/conversion devices of the vehicle with conventional and hybrid propulsion. It has also involved the analysis of energy management strategies currently available in the literature, adopted on road vehicles. Then, it has been formulated an "off-line" energy management algorithm, that is based on the knowledge of a fixed electric loads activation sequence and a fixed drive cycle of the veicle. The related activity has been the formulation and the solution of a global optimization problem (particularly for conventional and hybrid power-split vehicles), the solution of finite dimensional nonlinear convex optimization problems, with equality and inequality constraints. A case-study for testing the proposed new strategy on a real commercial hybrib power-split vehicle (Toyota Prius) has been reported.

Novel Approaches for Energy Management Strategies of Hybrid Electric Vehicles and Comparison with Conventional Solutions

Energies, 2022

Well-designed energy management strategies are essential for the good operation of Hybrid Electric Vehicles (HEVs) in terms of fuel economy and pollutant emissions reduction, regardless of the specific powertrain architecture. The goal of this paper is to propose two innovative supervisory control strategies for HEVs derived from different optimization algorithms and to assess HEVs’ fuel consumption reduction (compared to conventional vehicles). These approaches are derived from the literature and modified by the authors to present novel algorithms for the optimization problem. One is based on Dynamic Programming (DP), here referred to as the Forward Approach to Dynamic Programming (FADP) and introduces a different implementation of the DP to achieve computational and accuracy benefits. The other is based on the Equivalent Consumption Minimization Strategy (ECMS) approach, and it adapts to the latest driving conditions using information gathered in a finite-length backward-looking h...

Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation

Energies, 2018

In this paper, identification of an appropriate hybrid energy storage system (HESS) architecture, introduction of a comprehensive and accurate HESS model, as well as HESS design optimization using a nested, dual-level optimization formulation and suitable optimization algorithms for both levels of searches have been presented. At the bottom level, design optimization focuses on the minimization of power loss in batteries, converter, and ultracapacitors (UCs), as well as the impact of battery depth of discharge (DOD) to its operation life, using a dynamic programming (DP)-based optimal energy management strategy (EMS). At the top level, HESS optimization of component size and battery DOD is carried out to achieve the minimum life-cycle cost (LCC) of the HESS for given power profiles and performance requirements as an outer loop. The complex and challenging optimization problem is solved using an advanced Multi-Start Space Reduction (MSSR) search method developed for computation-intensive, black-box global optimization problems. An example of load-haul-dump (LHD) vehicles is employed to verify the proposed HESS design optimization method and MSSR leads to superior optimization results and dramatically reduces computation time. This research forms the foundation for the design optimization of HESS, hybridization of vehicles with dynamic on-off power loads, and applications of the advanced global optimization method.

A General Approach to Energy Optimization of Hybrid Electric Vehicles

IEEE Transactions on Vehicular Technology, 2000

This paper approaches the problem of optimizing energy consumption onboard hybrid vehicles in a general way, considering the main issues to be solved in their conceptuality and, therefore, that are often abstracted from the actual structure of the particular drive train that the authors considered. The methods that were described are a harmonization of those used by the authors over the last several years; therefore, although being rather general, they are far from describing the state of the art of scientific literature on this topic. Both parallel and series structures are covered; for either structure, the effect of different functions on management strategies (e.g., pure-electric drive and plug-in recharge capabilities) are discussed. Some more details are supplied in the Case Studies section of this paper, where some of the authors' past experiences are reconsidered in terms of the general approach proposed in this paper.

Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review

Hybrid Vehicles have experienced major modifications since the last decade. Smart grid success with combination of renewable energy exclusively depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation. Recent technical studies regarding various optimization strategies related to PHEV integrated smart grid; such as control and battery charging, vehicle-to-grid (V2G), unit commitment, charging infrastructures, integration of solar and wind energy and demand management prove that electrification of transportation as a rapidly growing field of research. This work presents a holistic review of all substantial research applying metaheuritics optimization for plug-in-hybrid electric vehicles. A summary on future perspective of metaheuristic algorithms is also provided, covering Cuckoo Search (CS), Harmony Search (HS), Artificial Bee Colony (ABC), etc. with a comprehensive reviews on previously applied methods and their performance for solving different real-world problems in the domain of PHEVs. Moreover, significant shifts towards hybrid and hyper metaheuristics are also highlighted.