Article
Energy & Fuels
Youssef Amry, Elhoussin Elbouchikhi, Franck Le Gall, Mounir Ghogho, Soumia El Hani
Summary: In electric vehicle charging systems, energy storage systems (ESS) are commonly used to supplement solar power and store excess energy. This article explores a hybrid system with a flywheel and PV for an EV workplace charging station. The study investigates the optimal sizing and operational cost of the hybrid system to make it more cost-effective. Comparative studies are carried out for different charging station models in different climate zones to determine the viability and cost-effectiveness of the proposed system.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Dariusz Borkowski, Piotr Oramus, Micha l Brzezinka
Summary: Battery energy storage systems (BESS) are a solution to address the negative impact of renewable energy sources (RES) on power systems, and they can improve the profitability of renewables by shifting energy to a higher price interval in the daily market (DM). This study proposes a dedicated control strategy for PV-BESS to maximize the DM revenue. The effectiveness of the algorithm is demonstrated through an example of real 1 MW PV data, showing a significant increase in the rate of return of the energy storage using the additional control mode.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Civil
Li Wang, Mince Li, Yujie Wang, Zonghai Chen
Summary: The paper focuses on optimizing the energy management strategy of hybrid energy storage systems by simultaneously optimizing the sizing of HESS and EMS parameters. The research uses AMPC and MOEA/D techniques for optimization, and employs the GWO-SVM method to enhance the applicability of EMS. The validation results demonstrate that the proposed method can improve system efficiency and extend battery life.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Thermodynamics
Tao Zhu, Richard G. A. Wills, Roberto Lot, Xiaodan Kong, Xingda Yan
Summary: This paper introduces a sizing method with sensitivity analysis for battery-supercapacitor hybrid energy storage systems to minimize vehicle-lifetime costs. By performing sensitivity analysis on eight parameters, the relative importance of each factor in practical engineering is quantified and compared. Results show that battery degradation accounts for around 89% of HESS costs, with vehicle driving range having the biggest impact on HESS costs.
Article
Green & Sustainable Science & Technology
Yapeng Li, Xiaolin Tang, Xianke Lin, Lech Grzesiak, Xiaosong Hu
Summary: Component sizing and energy management are crucial for minimizing vehicle costs and maximizing energy efficiency in electrified vehicles. Hierarchical optimization framework and convex optimization methods are effective approaches to tackle these challenges.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Chemistry, Physical
Xingyu Zhou, Chao Sun, Fengchun Sun, Chuntao Zhang
Summary: Due to the dynamic randomness of traffic flow, driving patterns and energy efficiency of electric vehicles (EVs) vary significantly. To optimize energy efficiency and reduce variability, this paper proposes an integrated stochastic optimization method for the design and control of EV powertrains.
JOURNAL OF POWER SOURCES
(2022)
Article
Chemistry, Physical
Xinchen Deng, Feng Wang, Bing Hu, Xianke Lin, Xiaosong Hu
Summary: Appropriate battery storage capacity is crucial for the performance and cost of residential energy systems. Two methods are developed to address long-term operational planning problems, and a new optimization method is proposed for obtaining optimal battery size within a year.
JOURNAL OF POWER SOURCES
(2022)
Article
Thermodynamics
Junyan Niu, Weichao Zhuang, Jianwei Ye, Ziyou Song, Guodong Yin, Yuanjian Zhang
Summary: This paper proposes an offline sizing method and an online energy management strategy for electric vehicles with a semi-active hybrid battery system (HBS). The proposed method optimizes the energy management and battery size of the vehicle through modeling and optimization algorithms. The simulation results demonstrate the effectiveness of the proposed method.
Article
Thermodynamics
Mingyao Yao, Bo Zhu, Nong Zhang
Summary: This paper presents a novel adaptive ECMS method for real-time optimal control of EREVs by transforming the fuel economy problem into convex optimization through variable substitution and polynomial fitting of fuel and battery consumption models. The proposed method achieves close-to-target terminal SOC maintenance, less than 2% difference in fuel economy compared to global optimization EMS, and significant improvements in computational efficiency compared to the shooting method.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Engineering, Electrical & Electronic
Abbas Mehraban, Ebrahim Farjah, Teymoor Ghanbari, Lauric Garbuio
Summary: This study proposes a method for determining the optimal size of a high-speed flywheel for an energy storage system for electric vehicles. By utilizing optimal control theory, the energy and filtering aspects interaction is considered, achieving a balance between long-term and short-term dynamics.
IET ELECTRIC POWER APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Mince Li, Li Wang, Yujie Wang, Zonghai Chen
Summary: This study utilizes a multi-objective grey wolf optimizer for sizing optimization of HESS and applies an adaptive real-time EMS, demonstrating notable advantages in battery protection and system efficiency.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2021)
Review
Chemistry, Physical
Babangida Modu, Md Pauzi Abdullah, Abba Lawan Bukar, Mukhtar Fatihu Hamza
Summary: Renewable energy systems (RESs) are crucial for meeting energy demand, and energy storage systems like batteries and hydrogen-based systems can address the issue of intermittent energy supply. This paper reviews recent advancements in hybrid RES with hydrogen storage, optimization methods, and energy management systems. It serves as a framework for researchers interested in investigating HRES with hydrogen storage.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Review
Energy & Fuels
Oussama Ouramdane, Elhoussin Elbouchikhi, Yassine Amirat, Ehsan Sedgh Gooya
Summary: The topic of microgrids (MGs) is a rapidly growing and highly promising field of research in terms of energy production quality, pollution reduction, and sustainable development. Research in this area covers a wide range of aspects including energy management, generation systems, energy storage devices, and electric vehicles. Integration of electric vehicles into national power grids and future microgrids is a key focus, with issues such as bi-directional power flow control and energy management being particularly important.
Article
Green & Sustainable Science & Technology
Irina Picioroaga, Madalina Luca, Andrei Tudose, Dorian Sidea, Mircea Eremia, Constantin Bulac
Summary: As climate changes intensify, the resilience of electricity supply systems becomes a major concern. To address this issue, a combination of renewable energy sources and energy storage systems is proposed to improve reliability and reduce the impact of outages on critical loads in remote microgrids.
Article
Automation & Control Systems
Rahmat Khezri, Amin Mahmoudi, Mohammed H. Haque
Summary: This article determines the optimal capacities of small wind turbine (SWT) and battery energy storage (BES) for a grid-connected household (GCH) with or without an electric vehicle (EV) to minimize the overall cost of electricity (COE). Rule-based home energy management systems (HEMSs) are developed to achieve this goal. Results show that SWT can effectively decrease the COE of the household, but the current battery prices may impact further reductions in COE.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Maryam Razi, Nikolce Murgovski, Tomas McKelvey, Torsten Wik
Summary: This paper presents an adaptive equivalent consumption minimization strategy (ECMS) and a linear quadratic tracking (LQT) method for optimal power-split control of a combustion engine and an electric machine in a hybrid electric vehicle (HEV). The study models SOC constraints and proposes sub-optimal analytic solutions with convex objective functions. Additionally, the controllers' robustness to measurement noise is considered, with simulation results comparing the effectiveness of the two controllers.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Maryam Razi, Nikolce Murgovski, Tomas McKelvey, Torsten Wik
Summary: This paper introduces predictive energy management of hybrid electric vehicles using computationally efficient multi-layer control. It involves optimizing gear, engine, battery, and electric machine decisions, and proposes efficient computation methods. The approach aims to optimize driving performance, prolong battery life, and improve fuel efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Qian Xun, Nikolce Murgovski, Yujing Liu
Summary: This paper proposes a cost-effective way to design and operate fuel cell hybrid electric trucks (FCHETs) through sequential convex programming to minimize costs. The results show that the power rating of the electric machine is drastically reduced when the delivered power is satisfied in a probabilistic sense.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Remi Lacombe, Sebastien Gros, Nikolce Murgovski, Balazs Kulcsar
Summary: Traditionally, the issues of bus bunching mitigation and vehicle energy management have been dealt with separately in the literature. This study presents a novel approach by formulating the optimal control problem for bus line eco-driving and regularity control as a smooth, multi-objective nonlinear program, enabling parallel computations and reducing communication loads between buses. By embedding this approach in a model predictive control, stochastic simulations show that the method achieves fast recoveries to regular headways and energy savings of up to 9.3% compared to traditional methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Ahad Hamednia, Nalin Kumar Sharma, Nikolce Murgovski, Jonas Fredriksson
Summary: This paper introduces a computationally efficient algorithm for eco-driving over long distances, which combines offline and online solutions to significantly reduce computational effort and achieve energy savings.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Nalin Kumar Sharma, Nikolce Murgovski, Esteban R. Gelso
Summary: This paper proposes a stochastic observer for estimating the power capability of a preceding heavy-duty vehicle, using its speed measurement and road slope information. An online learning approach is used to solve a chance-constrained optimization problem considering uncertainties. The effectiveness of the proposed observer is demonstrated in case studies on real road topographies, showing its robustness against uncertainties.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Thermodynamics
Fei Ju, Nikolce Murgovski, Weichao Zhuang, Xiaosong Hu, Ziyou Song, Liangmo Wang
Summary: This paper addresses the energy management problem of a power-split hybrid electric vehicle (HEV) with planetary gear sets. A mixed-integer global optimal control problem is formulated, and convex modeling is presented to reformulate the problem as a two-step program. The alternating direction method of multipliers (ADMM) algorithm is employed to optimize the engine switching and battery power decisions. Simulation results show significant fuel savings and computational efficiency compared to heuristic and dynamic programming methods. An ADMM-MPC method is also developed for real-time control with promising results.
Article
Engineering, Electrical & Electronic
Fei Ju, Nikolce Murgovski, Weichao Zhuang, Qun Wang, Liangmo Wang
Summary: This paper designs a predictive cruise controller (EC) for electric vehicles to enhance energy efficiency and battery lifetime. Simulation results show that the proposed controller performs suboptimally compared to the globally optimal solution. An enhanced EC is developed for practical scenarios, achieving energy saving and battery life extension compared to the intelligent driving model.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Ahad Hamednia, Nikolce Murgovski, Jonas Fredriksson, Jimmy Forsman, Mitra Pourabdollah, Viktor Larsson
Summary: This article explores optimal battery thermal management, charging, and eco-driving strategies for improving the grid-to-meter energy efficiency of battery electric vehicles (BEVs). An optimization problem is formulated to find the best trade-off between trip time and charging cost. The dynamics in driving and charging modes are modeled using different functions and decision-making is done in a spatial domain for driving and a temporal domain for charging. The proposed algorithm achieves a 44% reduction in trip time, including driving and charging times, compared to a case without active battery heating/cooling.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Mechanical
Fei Ju, Nikolce Murgovski, Weichao Zhuang, Liangmo Wang
Summary: This paper presents two nonlinear model predictive control methods for integrated propulsion and cabin-cooling management in electric vehicles. The proposed methods optimize system-level performance by minimizing battery energy consumption while maintaining cabin-cooling comfort. The results show that both methods offer significant energy benefits and maintain driving and thermal comfort. Additionally, the co-MPC method achieves comparable performance with reduced computation time compared to the joint MPC method.
Article
Engineering, Civil
Remi Lacombe, Sebastien Gros, Nikolce Murgovski, Balazs Kulcsar
Summary: This paper presents a distributed optimization procedure for the cooperative eco-driving control problem of a platoon of electric vehicles. Individual optimal trajectories are generated for each platoon member to account for heterogeneity and road slope. The proposed control strategy is privacy-preserving and can be deployed by any group of vehicles spontaneously while driving.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Anand Ganesan, Sebastien Gros, Nikolce Murgovski
Summary: This paper presents numerical strategies for a computationally efficient energy management system that co-optimizes the power split and gear selection of a hybrid electric vehicle (HEV). The proposed strategies, namely Selective Relaxation Approach (SRA) and Round-n-Search Approach (RSA), are compared with two benchmark strategies using rule-based gear selection and dynamic programming. The results show that both SRA and RSA achieve significant cost reduction compared to the rule-based strategy and come close to the performance of the dynamic programming solution.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Wei Du, Nikolce Murgovski, Fei Ju, Jingzhou Gao, Shengdun Zhao
Summary: This paper proposes a cost-effective power management strategy for dual electric machine coupling propulsion trucks using V2I communication data. A bilevel program is formulated where the high-level optimizes operation mode implicitly, and the low-level computes an explicit power distribution policy. Stochastic model predictive control (SMPC) strategy is employed at the high level, with position dependent stochastic velocity predictors developed using limited historical data. The proposed predictors are compared with a benchmark in simulations, showing a reduction in driving cost by 3.36% and 4.26% respectively.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Automation & Control Systems
Adrian Ilka, Nikolce Murgovski
Summary: This article presents novel developments in output-feedback stabilization for linear time-invariant systems within the framework of linear quadratic regulator (LQR). The necessary and sufficient conditions for output-feedback stabilizability are derived, followed by the proposal of a novel iterative Newton's method and a computationally efficient modified approach. The proposed modified approach guarantees convergence from a stabilizing state feedback to a stabilizing output-feedback solution and successfully solves high-dimensional problems. Numerical examples demonstrate the effectiveness of the proposed methods.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Toheed Ghandriz, Bengt Jacobson, Nikolce Murgovski, Peter Nilsson, Leo Laine
Summary: This paper proposes a real-time predictive energy management strategy for hybrid electric heavy vehicles, using a combination of model predictive control and sequential programming to optimize vehicle velocity and battery state of charge trajectories. By comparing the performance with two different sequential quadratic programs, it is found that the developed sequential linear program is faster and simpler in providing trajectories close to the best found by nonlinear programming.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)