Series Hybrid Research Articles

Closed‐Loop Recyclable and Extrusion Reprocessable Thermosets Enabled by Guanylthiourea Structure

AbstractPlastic recycling is a critical step toward improving waste management and achieving economic recycling. Here, a thermoset crosslinked by guanythiourea structure (GTUH network) is reported, that addresses the recycling issue of thermosets by serial hybridization of thiourea and guanidine urea. The dual dissociative dynamic exchange reaction of guanamine urea and thiourea, combined with non‐covalent hydrogen bonding interactions, endows the network with rapid relaxation ability. GTUH networks, in particular, can be recycled through continuous extrusion processing due to multiple reversible mechanisms, as opposed to hot pressing alone. Even if reprocessed by hot pressing, only 5 min at 140 °C and 10 MPa are required. The oxidation enhancement mechanism of thiourea contributes to maintaining or even improving the mechanical properties of the recycled network. Moreover, the dynamic reactions of guanythiourea structure allow for closed‐loop chemical recycling of the network. Research into recyclable carbon fiber‐reinforced composites indicates promising potential applications for this material in the circular economy and resources.

Parallel–Serial Robotic Manipulators: A Review of Architectures, Applications, and Methods of Design and Analysis

Parallel–serial (hybrid) manipulators represent robotic systems composed of kinematic chains with parallel and serial structures. These manipulators combine the benefits of both parallel and serial mechanisms, such as increased stiffness, high positioning accuracy, and a large workspace. This study discusses the existing architectures and applications of parallel–serial robots and the methods of their design and analysis. The paper reviews around 500 articles and presents over 150 architectures of manipulators used in machining, medicine, and pick-and-place tasks, humanoids and legged systems, haptic devices, simulators, and other applications, covering both lower mobility and kinematically redundant robots. After that, the paper considers how researchers have developed and analyzed these manipulators. In particular, it examines methods of type synthesis, mobility, kinematic, and dynamic analysis, workspace and singularity determination, performance evaluation, optimal design, control, and calibration. The review concludes with a discussion of current trends in the field of parallel–serial manipulators and potential directions for future studies.

Extending battery lifetime of electric-hydraulic hybrid wheel loader through system parameter optimization

Parallel electric hydraulic hybrid powertrain (PEHH) is a promising substitute for electric direct drive to extend battery lifetime. The convex programming (CP) based simultaneous optimization method has been adopted in electric hybrid system parameter optimization, but it is difficult to extend it for PEHH due to its non-convexity. In this paper, a combined exhaustive search – convex programming (ES-CP) system parameter optimization method is proposed to address the non-convexity of PEHH system parameter optimization problem. In this method, the PEHH system parameter optimization problem is modeled and reformulated in convex form and the convex part is decoupled from the optimization problem. The CP method is used for the convex part and the ES method is used for the remained non-convex part. The ES-CP method is applied to the PEHH powertrain to extend its battery lifetime. Optimization results show that the battery lifetime of the ES-CP optimized PEHH system is 6.8% longer than that of the non-optimized system. The computing time of ES-CP is 97% lower than Latin hypercube sampling and 90% lower than genetic algorithm methods.

The Design of Improved Series Hybrid Power System Based on Compound-Wing VTOL

Hybrid power systems are now widely utilized in a variety of vehicle platforms due to their efficacy in reducing pollution and enhancing energy utilization efficiency. Nevertheless, the existing vehicle hybrid systems are of a considerable size and weight, rendering them unsuitable for integration into 25 kg compound-wing UAVs. This study presents a design solution for a compound-wing vertical takeoff and landing unmanned aerial vehicle (VTOL) equipped with an improved series hybrid power system. The system comprises a 48 V lithium polymer battery(Li-Po battery), a 60cc internal combustion engine (ICE), a converter, and a dedicated permanent magnet synchronous machine (PMSM) with four motors, which collectively facilitate dual-directional energy flow. The four motors serve as a load and lift assembly, providing the requisite lift during the take-off, landing, and hovering phases, and in the event of the ICE thrust insufficiency, as well as forward thrust during the level cruise phase by mounting the variable pitch propeller directly on the ICE. The entire hybrid power system of the UAV undergoes numerical modeling and experimental simulation to validate the feasibility of the complete hybrid power configuration. The validation is achieved by comparing and analyzing the results of the numerical simulations with ground tests. Moreover, the effectiveness of this hybrid power system is validated through the successful completion of flight test experiments. The hybrid power system has been demonstrated to significantly enhance the endurance of vertical flight for a compound-wing VTOL by more than 25 min, thereby establishing a solid foundation for future compound-wing VTOLs to enable multi-destination flights and multiple takeoffs and landings.

Degradation Diagnosis and Control Strategy for a Diesel Hybrid Powertrain Considering State of Health

Hybrid electric vehicles (HEV) are a practical choice for energy saving in the transportation field. Degradation diagnosis (DD) is one of the main methods to guarantee system robustness. However, the classical DD methods cannot meet the requirements of HEV due to their system complexity. In this study, a novel Prognostics and Health Management (PHM) study was conducted to face these challenges. Firstly, a physical P2 HEV model with a rule-based controller was built, and its diesel engine sub-model was simplified by a neural network (NN) to ensure real-time performance of the degradation prognostics. Secondly, a degradation prognostics method based on gray relation analysis–principal component analysis (GRA-PCA) was illustrated, which could confirm degradation 2 s after the health index fell below the threshold. Finally, a degradation tolerance strategy based on long short term memory–model predictive control (LSTM-MPC) was performed to optimize vehicle speed tracing with minimal energy consumption and was validated by three cases. The result shows that the energy consumption stayed nearly unchanged for the engine degradation case. For the battery degradation case, the tracing error was reduced by 11.7% with 4.3% more energy consumption. For combined degradation, the strategy achieved a 12.3% tracing error reduction with 3.7% more energy consumption. The suggested PHM method guaranteed vehicle power performance under degradation situations.

Enhancing hosting capacity for electric vehicles in modern power networks using improved hybrid optimization approaches with environmental sustainability considerations

The increasing adoption of electric vehicles (EVs) presents both opportunities and challenges for power networks. While EVs have the potential to reduce carbon emissions, accommodating their growing power demand requires careful planning to prevent overloading and mitigate environmental impacts. This paper introduces an integrated hosting capacity model to facilitate higher EV penetration while maintaining environmental standards. In addition to EV charging stations, the model incorporates transmission lines, reactive power compensators, energy storage systems, and thyristor-controlled series compensators to ensure a reliable power supply. The model aims to maximize EV charging station deployment, minimize greenhouse gas emissions, and optimize net present value through hosting capacity strategies. Three hosting capacity plans are proposed to analyze the impact of prioritizing one of these objectives over the others in network configurations. Accurate EV demand forecasting is critical for this model, and a swarm intelligence forecasting algorithm is proposed to explore various forecasting approaches. The model is complex and involves nonlinear multi-objective optimization. To solve it, a new hybrid optimization algorithm is introduced, combining the features of the Marine Predators Algorithm and the Honey Badger Algorithm. Three hybridization schemes—Series Hybrid Scheme, Population Division Scheme, and Switching Strategy Scheme—are developed to address the optimization challenges effectively. The results show that the first and second hybridization schemes are the most effective for solving the EV load forecasting models, with a robustness of at least 90%. In contrast, the robustness of the third scheme reaches only 30% in some models. Simulation studies on the IEEE 9-bus network and the IEEE 30-bus system validate the model’s effectiveness in integrating EVs while achieving environmental sustainability objectives. The findings show the superiority of the proposed hybrid schemes in solving the hosting capacity model in terms of finding optimal solutions. However, the third scheme required less computing time than the others, with its convergence time being at least 33.3% shorter.

Active Disturbance Rejection Control of Engine Speed in Series Hydraulic Hybrid Power System

Abstract: In this paper, a novel series hydraulic hybrid powertrain is proposed for a three-axis all-terrain vehicle. The engine drives two variable displacement pumps responsible for driving and steering, respectively. A variable displacement motor is connected to the ring gear of the planetary coupling mechanism to drive the vehicle and a fixed-displacement motor is connected to the sun gear to steer the vehicle. The active disturbance rejection control with feedforward control is employed to control the engine speed. The engine speed is controlled in a close-looped manner by adjusting the engine throttle. The controller parameters are decided by analyzing the influence of each parameter on the controller performance by means of the control variable method. The simulation results indicate that the proposed control strategy enables the vehicle to obtain better engine speed following and anti-disturbance performance. An all-terrain prototype is established and field tests are carried out to verify the effectiveness of the design and control strategy of the series hydraulic hybrid powertrain for the all-terrain vehicle.

A heavy-duty tracked vehicle model with a reduced feasible domain for motion tracking control considering dynamic characters of hybrid powertrain

Motion tracking control is an essential part of heavy-duty unmanned tracked vehicles to realize autonomous mobility, which adjusts the vehicle motion in real-time by controlling the driving torques. Achieving accurate motion tracking strongly depends on the use of a precise vehicle dynamic model. To support the motion tracking ability, a vehicle dynamic model with a reduced feasible domain is proposed for heavy-duty unmanned tracked vehicles. Firstly, a vehicle dynamic model is established based on the vehicle kinematics and dynamics. Building upon the established vehicle dynamic model, a graph neural network (GNN) is employed to reduce the feasible domain of the vehicle dynamic model, specifically focusing on the limitation of the powertrain. The powertrain components and their interconnections are abstracted into a graph, which is analyzed to study the interactions between the components using the GNN. Finally, the proposed vehicle dynamic model with a reduced feasible domain is verified through actual heavy-duty tracked vehicle experiments in various cases. Compared with the back propagation neural network, the evaluation error of the driving torque decreased by 25.86%. Results show that the proposed vehicle dynamic model with a reduced feasible domain is closer to the performance of the actual heavy-duty tracked vehicle and their powertrain. And the vehicle dynamic model accurately reduces the solution time of the motion tracking control, resulting in improved accuracy and efficiency of the motion tracking control.

Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle

Hybrid electrical vehicles (HEV) should be designed somehow torque is smooth. Because torque ripple not only reduces control precision but also increases elements vibration that causes acoustic noise, mechanical instability and early aging parts. Furthermore, torque per volume should be maximized and heat removal should be accomplished without torque weakening. It is proposed the volume and internal dimensions are determined due to the thermal considerations and maximize torque per volume. The mentioned application is neglected heat removal so volume is constant. Therefore, HEV is manufactured by two objective functions: either minimum fluctuations or maximum average torque. In this paper series hybrid excitation synchronous machine (SHESM) is utilized as HEV. Two-objective optimization problems are solved by MOEA/D, NSGA II, PESA II and SPEA II algorithms based on a two-dimensional (2-D) model. The performance indices of optimal structure are evaluated by 2-D and confirmed by numerical method.

Unlocking the potential of electric and hybrid tractors via sensitivity and techno-economic analysis

The majority of agricultural vehicles in use today still rely on diesel-based propulsion, a major source of air pollution. Electrification is seen as a potential solution for decarbonizing these off-road vehicles but is hampered by higher upfront costs in energy storage and charging infrastructure. To better quantify these barriers, this paper proposes a techno-economic tool that can assist farmers in evaluating the total costs of ownership of electric and hybrid tractors. A pragmatic simulation model of the tractor is developed to predict the annual energy/fuel consumption and NOx emissions, while an economic model estimates the total acquisition, operation, and maintenance costs. For managing the energy in hybrid tractors, a new power split strategy based on model predictive control is developed, allowing the designer to balance energy efficiency and NOx emissions, while taking into account operational constraints of the electric powertrain. Additionally, we propose novel decision maps that allow farmers to quickly identify operating regions (in term of average load and yearly working time) where the deployment of electric/hybrid tractors is economically viable. To account for variability in the tractor’s operational conditions, we conduct both a deterministic sensitivity analysis with multi-parameter variation and a stochastic analysis of the total cost of ownership. The tool is validated with different mission profiles based on data from a California farm. The results show that, compared to diesel powertrains, electric tractors are more cost-effective for light-duty farming activities (engine loads less than 20%). On the other hand, hybrid powertrains are more economical for medium-duty tasks, where engine loads range from 20% to 60%.

Dynamic Modeling and Control Strategy Optimization of a Volkswagen Crafter Hybrid Electrified Powertrain

This article studies the transformation and assembly process of the Volkswagen (VW) Crafter from conventional to hybrid vehicle of the department of vehicles engineering, University of Debrecen, and uses a computer-aided simulation (CAS) to design the vehicle based on the real measurement data (hardware-in-the-loop, HIL method) obtained from an online CAN bus data measurement platform using MATLAB/Simulink/Simscape and LabVIEW software. The conventional vehicle powered by a 6-speed manual transmission and a 4-stroke, 2.0 Turbocharged Direct Injection Common Rail (TDI CR) Diesel engine and the transformed hybrid electrified powertrain are designed to compare performance. A novel methodology is introduced using Netcan plus 110 devices for the CAN bus analysis of the vehicle’s hybrid version. The acquired raw CAN data is analyzed using LabVIEW and decoded with the help of the database (DBC) file into physical values. A classical proportional integral derivative (PID) controller is utilized in the hybrid powertrain system to manage the vehicle consumption and CO2 emissions. However, the intricate nonlinearities and other external environments could make its performance unsatisfactory. This study develops the energy management strategies (EMSs) on the basis of enhanced proportional integral derivative-based genetic algorithm (GA-PID), and compares with proportional integral-based particle swarm optimization (PSO-PI) and fractional order proportional integral derivative (FOPID) controllers, regulating the vehicle speed, allocating optimal torque and speed to the motor and engine and reducing the fuel and energy consumption and the CO2 emissions. The integral time absolute error (ITAE) is proposed as a fitness function for the optimization. The GA-PID demonstrates superior performance, achieving energy efficiency of 90%, extending the battery pack range from 128.75 km to 185.3281 km and reducing the emissions to 74.79 gCO2/km. It outperforms the PSO-PI and FOPID strategies by consuming less battery and motor energy and achieving higher system efficiency.

A Screw Theory Approach for Instantaneous Kinematic Analysis of Parallel–Serial Manipulators

Abstract The paper presents an approach to perform an instantaneous kinematic analysis of parallel–serial (hybrid) manipulators using screw theory. In this study, we focus on non-kinematically redundant manipulators that include a single parallel mechanism. The proposed systematic procedure allows deriving Jacobian matrices for such manipulators, which provide mathematical relations between the end-effector velocities and speeds in the actuated joints. A generalized structure of the obtained matrices also reflects the constrained motions of the end-effector and the parallel mechanism. To illustrate the developed techniques, we consider three examples where we analyze three well-known parallel–serial manipulators with six, five, and four degrees-of-freedom. Following the proposed method, we determine Jacobian matrices for each manipulator. Next, we apply the presented approach for velocity analysis of a novel parallel–serial manipulator with five degrees-of-freedom. Numerical simulations validate the proposed theoretical techniques. The suggested approach represents the basis for subsequent singularity and performance analysis, and it can be adapted to hybrid manipulators with other architectures.

Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Partial Hybrid Powertrain

Abstract The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept transport aircraft representative of technology anticipated for a 2040 entry-into-service date. The powertrain consists of a single thrust-producing geared turbofan engine with generators driving a series/parallel partial hybrid power/propulsion system. The architecture includes 16 underwing contrarotating fans, eight on each side. The distributed fans can be used by the flight control system to augment or replace the rudder function. This paper sets up the optimal control problem of setpoint determination for individual wingfans in the distributed propulsion system, accounting for electrical string efficiencies, saturations, and failures. The solution minimizes power consumption while maintaining thrust and torque on the airframe for maneuvering. Additionally, thrust that would have been lost due to temporary fan speed or power saturation is optimally redistributed to maintain overall desired thrust and torque on the aircraft. A simulation of a coordinated turn utilizing the distributed electric propulsion for yaw rate control in a multiple wingfan failure scenario demonstrates the robustness of the powertrain design to failures and helps define its limitations.

Capacity configuration of fuel cell hybrid vehicles using enhanced multi-objective particle swarm optimization with competitive mechanism

A well-designed hybrid powertrain is crucial for ensuring the safe, efficient, and durable operation of fuel cell hybrid vehicles. This paper introduces a modular design approach for powertrains, utilizing a Competitive mechanism-based Multi-Objective Particle Swarm Optimization (CMOPSO) algorithm integrated with nested dynamic programming. In this approach, the upper layer employs the CMOPSO algorithm to design the powertrain system, while the lower layer optimizes power coordination for each proposed design. This two-layer optimization framework considers factors such as vehicle economy and durability. Under WLTP conditions, the capacity configuration results are a fuel cell with a rated power of 22 kW, 100 batteries in series, and 7 batteries in parallel. Furthermore, the modular approach outperforms three other algorithms in terms of solution count, diversity, and overall performance metrics. The study also highlights that the vehicle’s power demand characteristics, influenced by different driving cycles, significantly affect capacity configuration results. Sensitivity analysis reveals that both the total operating cost and manufacturing cost of the vehicle are most sensitive to variations in the fuel cell rated power.

CO2 emission characteristics of China VI hybrid vehicles

As the ownership of hybrid vehicles soars, accurately predicting and assessing CO2 emissions become crucial. This study utilized the AVL portable emission measurement system (PEMS) to reveal the actual CO2 emission of three types of hybrid vehicles. Firstly, engine speed is a key factor influencing CO2 emissions of range-extended electric vehicle (REEV) and plug-in hybrid electric vehicle (PHEV), while vehicle specific power (VSP) affects HEV. Secondly, in terms of fuel consumption, when the battery levels of REEV and PHEV are low, their fuel consumption tends to be higher than that of HEV. Specifically, the CO₂ emission factor (the amount of CO2 emitted by a vehicle per unit distance during operation) ratios of REEV to PHEV range from 1.19 to 1.89, while the ratios of REEV to HEV are between 1.41 and 2.57. Thirdly, in terms of NOX control, HEV performed significantly worse.

Experimental study on the optimization of operating conditions for hybrid powertrain gasoline engines

With the rapid expansion of the market for hybrid vehicles, the development of dedicated hybrid powertrain engines has become an important research direction. This study focuses on the techniques to improve the fuel economy of dedicated hybrid powertrain operating conditions of 2000 rpm, 110 Nm. Turbocharging can enhance the performance and fuel economy of gasoline engines while reducing emissions. However, intake boosting increases the pressure and temperature of the mixture in the cylinder at the compression end timing, leading to a higher risk of knock, which is not conducive to the safety and fuel consumption reduction of gasoline engines. Low-temperature combustion with mixture dilution can effectively reduce the occurrence of knock and NOx emissions. In this study, the effects of EGR and VVT strategies as different dilution methods on the combustion of turbocharged gasoline engines were investigated. The experimental results indicate that both EGR and VVT can achieve mixture dilution in the cylinder, reducing the combustion temperature and thus lowering NOx emissions. Furthermore, advancing the ignition timing results in CA50 trending towards the optimal fuel consumption point, shortening the combustion duration CA10–90, and reducing ISFC. Compared to VVT, EGR can better suppress knock, leading to an earlier ignition phase CA50, a shorter combustion duration, and ultimately less fuel consumption. The research findings provide technical support for the optimization of dedicated hybrid powertrain operating conditions.

A Simplified 4-DOF Dynamic Model of a Series-Parallel Hybrid Electric Vehicle

To research the dynamic response of a new type of dedicated transmission for a hybrid electric vehicle, a detailed dynamics model should be built. However, a model with too many degrees of freedom has a negative effect on controller design, which means the detailed model should be simplified. In this paper, two dynamic models are established. One is an original and detailed powertrain dynamics model (ODPDM), which can capture the transient response, and it is validated that the ODPDM can be used to accurately describe the real vehicle in some specific operating conditions. The other is a simplified torsional vibration dynamics model to study the torsional vibration characteristics of the hybrid electric vehicle. Compared with the full-order model, which is based on the ODPDM, the simplified model has a very similar vibration in low frequency. This study provides a basis for further vibration control of the hybrid powertrain during the process of a driving-mode switch.

Feasibility Study on MHEV Application for Motorbikes: Components Sizing, Strategy Optimization through Dynamic Programming and Analysis of Possible Benefits

Reducing CO2 emissions is becoming a particularly important goal for motorcycle manufacturers. A fully electric transition still seems far away, given the difficulties in creating an electric motorcycle with an acceptable range and mass. This opens up opportunities for the application of hybrid powertrains in motorcycles. Managing mass, cost, and volume is a challenging issue for motorcycles; therefore, an MHEV architecture represents an interesting opportunity, as it is a low-complexity and low-cost solution. Firstly, in this work, an adequate sizing of the powertrain components is studied for the maximum reduction in fuel consumption. This is performed by analyzing many different system configurations with different hybridization ratios. A 1D simulation of the motorcycle traveling along the homologation cycle (WMTC) is performed, and the powerunit use strategy is optimized for each configuration using the Dynamic Programming technique. The results are analyzed in order to highlight the impact of kinetic energy recovery and engine load-point shifting on fuel consumption reduction. The results show the applicability of MHEV technology to road motorcycles, thus providing a useful tool to analyze the cost/benefit ratio of this technology. The developed methodology is also suitable for different vehicles once a specific test cycle is known.

Hybrid electric aircraft design with optimal power management

The aviation industry has continuously improved its fuel efficiency over the last decades with innovations in technology, design and operation. Further improvements are becoming more difficult as current technology reaches complete maturity. Electrification of road vehicles is predicted to completely replace combustion engines in vehicles. As the efficiency and reliability of electric batteries and motors improve, so does the case for electric propulsion systems in aircraft. Jet fuel carries significantly more energy per weight than current state of the technology batteries, making complete replacement of fuel challenging. Hybrid electric propulsion, where both fuel and batteries are used to power propulsion systems could be feasible and improve fuel efficiency. Hybrid electric powertrains use electric power to reduce the power demands from the combustion engine. Electric batteries are discharged and charged during the operation based on power requirements.This paper presents an aircraft design method that includes optimized power management in the design loop. Power management determines battery discharging and charging throughout the design mission to reduce overall fuel consumption. Power management optimization provides the necessary feedback on battery and fuel performance to design battery pack size. This method is applied to regional aircraft, which typically fly the shortest routes of a commercial airline fleet. These short routes have proportionally longer climb and descent segments. These characteristics of regional aircraft routes lead to wider variations in power during operation, where hybrid electric powertrains are the most beneficial.The proposed hybrid electric aircraft design method finds that a serial hybrid electric regional aircraft could achieve significant fuel efficiency improvements to current regional aircraft. This result is in contrast of the current literature, which requires significant improvements to battery energy density, power distribution efficiency and electric motor efficiency to achieve similar fuel performance results. The hybrid electric regional aircraft does not outperform a traditional turboprop aircraft designed with identical objectives. The turboprop aircraft design improves even greater fuel efficiency improvements over current regional turboprop aircraft. This suggests two pathways are possible; the propulsion system of the next generation of regional aircraft could still be non-electric and achieve improved fuel burn improvements considering current technology or serial hybrid-electric powertrains configurations could be adopted in an expanded time horizon if optimistic technology development is done on battery power density to match the possible improvements of the proposed turboprop aircraft.

Ground test protection strategy for the 100 kW series hybrid electric propulsion system

With the goal of lower emissions, hybrid electric propulsion (HEP) aircraft is considered to be a promising solution, with the advantages of being more environmentally friendly and efficient. Moreover, superior reliability and good safety of the HEP systems is vital to ensure a safe flight. For this purpose, this article presents several successful case studies on overspeed, overvoltage/overcurrent, and communication protection with the combination of theory and experimental data. Given the practical application capability of fault protection, this article established a 100 kW HEP platform and designed an effective system level fault protection architecture, which consists of physical layer, decision layer and execution layer. Experimental studies have been conducted on the turboshaft engine overspeed, electrical architecture overvoltage/overcurrent, communication faults to verify the effectiveness of the proposed fault protection scheme. The test results have shown that the proposed strategy can effectively deal with various fault situations mentioned above to prevent the entire HEP aircraft system from becoming paralyzed, thus improving the reliability and safety of the system.