Browsing by Author "Zhang, Jinning"

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    Assessment of engine operability and overall performance for parallel hybrid electric propulsion systems for a single-aisle aircraft
    (American Society of Mechanical Engineers, 2021-09-16) Kang, Sangkeun; Roumeliotis, Ioannis; Zhang, Jinning; Pachidis, Vassilios; Broca, Olivier
    This paper aims to assess the gas turbine operability and overall hybrid electric propulsion system performance for a parallel configuration applied to a 150 passenger single-aisle aircraft. Two arrangements are considered: one where the low pressure shaft is boosted and one where the high pressure shaft is boosted. For identifying limits in the hybridization strategy steady state and transient operation are considered and the hybridization effect on compressor operability is determined. Having established the electric power on-take limits with respect to gas turbine operation the systems performance at aircraft level is quantified for the relevant cases. Different power management strategies are applied for the two arrangements and for different power degrees of hybridization. The results indicate that despite the fact that pollutant emission and fuel consumption may improved for hybrid propulsion, this comes at the cost of reduced payload and operability margins. Boosting the low pressure shaft may give the highest engine performance benefits but with a significant weight penalty, while the low pressure compressor system operability is negatively affected. On the other hand boosting the high pressure shaft provides lower engine performance benefits but with smaller weight penalty and with less operability concerns.
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    ItemOpen Access
    Assessment of engine operability and overall performance for parallel hybrid electric propulsion systems for a single-aisle aircraft
    (American Society of Mechanical Engineers, 2022-01-04) Kang, Sangkeun; Roumeliotis, Ioannis; Zhang, Jinning; Broca, Olivier; Pachidis, Vassilios
    This paper aims to assess the gas turbine operability and overall hybrid electric propulsion system (HEPS) performance for a parallel configuration applied to a 150 passenger single-aisle aircraft. Two arrangements are considered: one where the low-pressure (LP) shaft is boosted and one where the high-pressure (HP) shaft is boosted. For identifying limits in the hybridization strategy, steady-state and transient operation are considered, and the hybridization effect on compressor operability is determined. Having established the electric power on-take limits with respect to gas turbine operation, the systems performance at aircraft level is quantified for the relevant cases. Different power management strategies (PMS) are applied for the two arrangements and for different power degrees of hybridization. The results indicate that despite the fact that pollutant emission and fuel consumption may improve for hybrid propulsion, this comes at the cost of reduced payload and operability margins. Boosting the LP shaft may give the highest engine performance benefits but with a significant weight penalty, while the LP compressor system operability is negatively affected. On the other hand, boosting the HP shaft provides lower engine performance benefits but with smaller weight penalty and with less operability concerns.
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    Aviation-to-grid flexibility through electric aircraft charging
    (IEEE, 2021-10-16) Guo, Zekun; Zhang, Jinning; Zhang, Rui; Zhang, Xin
    This paper proposes a new concept of Aviation-to-Grid (A2G) that utilizes electric aircraft (EA) charging to provide flexibility to the power grid. Smart EA charging system with battery swap method is developed using PV, gas turbine, and grid electricity. Hourly energy dispatch strategy is produced based on the mixed integer linear programming method to meet electrified aviation and provide A2G frequency response. Case studies are conducted in 8 major UK airports considering seasonal flight schedules and power system scenarios. Results show that the EA charging system can provide effective primary and secondary frequency response to improve the frequency nadir by 0.2 - 0.3 Hz under grid disturbance. The total A2G frequency response capacity across the 8 UK airport can reach up to 1,300 MW overnight and up to 900 MW daytime. Annual A2G frequency response revenue is 46.58 million pounds, which can cover 19.8% to 30% of EA charging costs.
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    Efficient and near-optimal global path planning for AGVs: a DNN-based double closed-loop approach with guarantee mechanism
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Zhang, Runda; Chai, Runqi; Chen, Kaiyuan; Zhang, Jinning; Chai, Senchun; Xia, Yuanqing; Tsourdos, Antonios
    In this article, a novel global path planning approach with rapid convergence properties for autonomous ground vehicles (AGVs) named neural sampling rapidly exploring random tree (NS-RRT*) is proposed. This approach has a three-layer structure to obtain a feasible and near-optimal path. The first layer is the data collection stage. Utilizing the target area adaptive rapidly exploring random tree (TAA-RRT*) algorithm to establish a collection of paths considering the initial noise disturbance. To enhance network generalization, an optimal path backward generation (OPBG) strategy is introduced to augment the dataset size. In the second layer, the deep neural network (DNN) is trained to learn the relationships between the states and the sampling strategies. In the third layer, the trained model is used to guide RRT* sampling, and an efficient guarantee mechanism is also designed to ensure the feasibility of the planning task. The proposed algorithm can assist the RRT* algorithm in efficiently obtaining optimal or near-optimal strategies, significantly enhancing search efficiency. Numerical results and experiments are executed to demonstrate the feasibility and efficiency of the proposed method.
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    Model-based fully coupled propulsion-aerodynamics optimization for hybrid electric aircraft energy management strategy
    (Elsevier, 2022-01-20) Zhang, Jinning; Roumeliotis, Ioannis; Zolotas, Argyrios
    Hybrid electric aircraft concepts are high in future aviation agenda to enabling reduced fuel consumption and emissions. However, the additional weight of the introduced battery and electrical components and sizing cascading effects will impact aircraft mission analysis performance. Therefore, the potential benefit of adopting hybrid electric aircraft will highly depend on the applied energy management strategy (EMS). This paper presents a three-layer propulsion-mission analysis-EMS integrated multi-objective optimization scheme for hybrid electric aircraft identifying feasible design aspects considering fully coupled propulsion-aerodynamics effects. The ‘propulsion’ layer comprises the propulsion system modelling, integration approaches, and performance synthesis using an Artificial Neural Network (ANN)-based gas turbine surrogate model. The ‘mission-analysis’ layer is designed for multi-energy sources hybrid electric aircraft mission analysis considering fully coupled propulsion-aerodynamic effects. The ‘EMS’ layer utilizes non-dominated sorting genetic algorithm II (NSGA-II) addressing the design trade-off, i.e., block fuel burn, energy consumption, emissions. The proposed scheme is applied to a typical narrow-body aircraft, Boeing 737–800, equipped with mechanically integrated hybrid electric parallel propulsion configuration to explore flight electrification in civil aviation. Moreover, sensitivity analysis of battery technology level and flight mission definition is followed providing insights to hybrid electric aircraft application scenarios. The EMS optimization results indicate that for short/medium haul aircrafts which operate in high altitude with long flight durations, fuel as consumable energy source is prone to be used in initial stages to reduce aircraft weight and lift-dependent drag, while battery as non-consumable energy is optimally allocated in final flight stages of descent and landing. The design of hybrid electric aircraft is highly sensitive to both flight mission definition and battery specific energy projections. With battery specific energy projections of 1500 Wh/kg for the year 2035, optimal block fuel burn reduction by −44.62%, −31.47% and −21.86% can be obtained at the flight range design of 1000 nmi, 1250 nmi and 1500 nmi respectively.
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    Nonlinear model predictive control-based optimal energy management for hybrid electric aircraft considering aerodynamics-propulsion coupling effects
    (IEEE, 2021-12-21) Zhang, Jinning; Roumeliotis, Ioannis; Zolotas, Argyrios
    Hybrid electric propulsion systems have been identified as the feasible solutions for regional jets and narrow-body aircrafts to reduce block fuel burn, emissions, and operating cost. In this paper, a Nonlinear Model Predictive Control based optimal energy management scheme (MPC-EMS) has been proposed to minimize the block fuel burn during flight. Firstly, the Artificial Neural Network (ANN) model is adopted to predict turbofan engine performance, meanwhile gas turbine-electrical powertrain integration is investigated and analyzed for typical operating conditions. Then, by combining a point-mass aircraft dynamic model, nonlinear model predictive control with Cross-Entropy Method (CEM) is proposed to obtain optimal energy management based on a fully coupled aerodynamics-propulsion hybrid electric aircraft model. Besides, this state-constrained optimal control problem is re-formulated as a state-unconstrained problem with penalty function to reduce the computational load. Finally, the proposed MPC-EMS algorithm is applied to Boeing 737-800 aircraft with mechanically parallel hybrid electric propulsion configuration to minimize the block fuel burn and compared with the optimization results using global Genetic Algorithm (GA) based EMS and Equivalent Consumption Minimization Strategy (ECMS). The simulation results indicate that the proposed MPC-EMS can effectively reduce the computational time compared with Global GA-based EMS while achieving global optimization performance with only a minor difference of 1.71% of block fuel burn and emissions reductions.
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    Performance and economic assessment of mechanically integrated parallel hybrid aircraft
    (American Society of Mechanical Engineers, 2022-10-28) Carpentier, Thibault; Zhang, Jinning; van Heerden, Albert S. J.; Roumeliotis, Ioannis
    In this study, a selection of environmental and economic considerations of mechanically integrated parallel hybrid (MIPH) electric propulsion systems for single-aisle civil transport aircraft are assessed. The environmental assessment focuses on the carbon dioxide and nitrogen oxide emissions with different power management strategies and levels of battery technology. In the economic study, the potential subsidies and tax incentives required to make these aircraft financially viable are determined. To capture the performance results, models of the propulsion systems and airframe were constructed using the Siemens Simcenter Amesim systems modelling software. The operating cost was then computed using adapted direct operating cost estimation methods. Battery replacement was incorporated by using a battery cycle aging model. The results showed that using a battery energy density of 300 Wh/kg will not provide any meaningful benefits. For 600 Wh/kg, fuel savings of up to 3% for missions below 650 nm could be obtained for a PMS where the electrical powertrain operates during takeoff, climb, and cruise. However, the NOx emissions were lowest for the takeoff and climb only PMS, implying a trade-off when selecting a PMS. Based on the cost results, it is determined that taxation on carbon emissions would have to increase at least 50-fold from its current levels for the most optimistic scenarios. Alternatively, considerable subsidies, representing large percentages of the purchase price of the aircraft, will be needed.
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    Profit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networks
    (Elsevier, 2022-11-15) Lai, Chun Sing; Chen, Dashen; Zhang, Jinning; Zhang, Xin; Xu, Xu; Taylor, Gareth A.; Lai, Loi Lei
    Large-scale integration of battery energy storage systems (BESS) in distribution networks has the potential to enhance the utilization of photovoltaic (PV) power generation and mitigate the negative effects caused by electric vehicles (EV) fast charging behavior. This paper presents a novel deep reinforcement learning-based power scheduling strategy for BESS which is installed in an active distribution network. The network includes fast EV charging demand, PV power generation, and electricity arbitrage from main grid. The aim is to maximize the profit of BESS operator whilst maintaining voltage limits. The novel strategy adopts a Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and requires forecasted PV power generation and EV smart charging demand. The proposed strategy is compared with Deep Deterministic Policy Gradient (DDPG), Particle Swarm Optimization and Simulated Annealing algorithms to verify its effectiveness. Case studies are conducted with smart EV charging dataset from Project Shift (UK Power Networks Innovation) and the UK photovoltaic dataset. The Internal Rate of Return results with TD3 and DDPG algorithms are 9.46% and 8.69%, respectively, which show that the proposed strategy can enhance power scheduling and outperforms the mainstream methods in terms of reduced levelized cost of storage and increased net present value.
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    Sustainable aviation electrification: a comprehensive review of electric propulsion system architectures, energy management, and control
    (MDPI, 2022-05-12) Zhang, Jinning; Roumeliotis, Ioannis; Zolotas, Argyrios
    The civil aviation sector plays an increasingly significant role in transportation sustainability in the environmental, economic, and social dimensions. Driven by the concerns of sustainability in the aviation sector, more electrified aircraft propulsion technologies have emerged and form a very promising approach to future sustainable and decarbonized aviation. This review paper aims to provide a comprehensive and broad-scope survey of the recent progress and development trends in sustainable aviation electrification. Firstly, the architectures of electrified aircraft propulsion are presented with a detailed analysis of the benefits, challenges, and studies/applications to date. Then, the challenges and technical barriers of electrified aircraft propulsion control system design are discussed, followed by a summary of the control methods frequently used in aircraft propulsion systems. Next, the mainstream energy management strategies are investigated and further utilized to minimize the block fuel burn, emissions, and economic cost. Finally, an overview of the development trends of aviation electrification is provided.
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    Techno-economic-environmental evaluation of aircraft propulsion electrification: Surrogate-based multi-mission optimal design approach
    (Elsevier, 2023-01-10) Zhang, Jinning; Roumeliotis, Ioannis; Zhang, Xin; Zolotas, Argyrios
    Driven by the sustainability initiatives in the aviation sector, the emerging technologies of aircraft propulsion electrification have been identified as the promising approach to realize sustainable and decarbonized aviation. This study proposes a surrogate-based multi-mission optimal design approach for aircraft propulsion electrification, which innovatively incorporates realistic aviation operations into the electric aircraft design, with the aim of improving the overall aircraft fuel economy over multiple flight missions and conditions in practical scenarios. The proposed optimal design approach starts with the flight route data analysis to cluster the flight operational data using gaussian mixture model, so that a concise representation of flight mission profiles can be achieved. Then, an optimal orthogonal array-based Latin hypercubes are employed to generate sampling points of design variables for electrified aircraft propulsion. The mission analysis is performed with coupled propulsion-airframe integration in order to propose energy management strategy for mission-dependent aircraft performance. Consequently, fuel economy surrogate model is established via support vector machines to obtain the optimal design points of electrified aircraft propulsion. For assessing the viability of novel propulsion technologies, techno-economic evaluation is conducted using sensitivity analysis and breakeven electricity prices under a series of environmental regulatory policy scenarios.