Regenerative Braking Energy Research Articles

Analysis of Regenerative Braking Energy Utilization in KfW i9000 Electric Trains on the Palur-Yogyakarta Operation

Abstract This study explores the potential assessment. of regenerative braking energy in the operation of Electric Multiple Units (EMU) on the Yogyakarta-Palur railway line, a 65.03 km. Prompted by a noticeable increase in passenger numbers in the Yogyakarta metropolitan buffer zone, the study calls for future energy management strategies, involving regenerative braking to reduce energy consumption. Utilizing a mathematical model implemented via MATLAB Simulink, the research encompasses complex train movement scenarios, considering variables such as acceleration values of 0.558 m/s2 and 1 m/s2, and deceleration values of -0.555 m/s2 and 0.36 m/s2. Speed limitations, travel patterns, and energy profiles are rigorously examined, along with incline influences, such as tangent angles of 0.0032 degrees and 0.0017 degrees. In segments like Purwosari-Solo Jebres, electrical energy consumption is quantified at 23.02 kWh, with regenerative braking energy at 1.42 kWh; in Maguwo-Brambanan, consumption is 15.28 kWh, with regenerative energy at 2.42 kWh. The peak power requirements and regenerative braking potentials were also determined, with values such as 619.9 kW and 225.7 kW, and 1785 kW and 198.2 kW respectively. The total electrical consumption for the routes from Palur to Yogyakarta and vice versa was found to be 325.52 kWh and 276.73 kWh, with energy recovery of 31.43 kWh and 26.6 kWh, and average energy recovery ratios of 9.66% and 9.61%.

Joint optimization of metro train timetable and stopping plan for the first service period: An integrated energy-efficient and time-saving model

This paper addresses the energy conservation challenge in metro systems during the first service period, characterized by large train headways and low passenger demands. A novel train timetabling method incorporating an express-local mode is proposed to maximize the overlap time between accelerating and braking trains, thereby facilitating the utilization of regenerative braking energy (RBE). Local and express trains depart alternately, with skip-stop strategies implemented for express trains. Considering the interests of operator and passengers for energy and travel time savings, a bi-objective model is proposed to jointly optimize train timetable and stopping plan. NSGA-II is applied to solve the model and obtain Pareto optimal solutions. Numerical experiments based on Ningbo Metro Line 1 data validate the effectiveness of proposed methods, showcasing significant enhancement in RBE utilization and notable reduction in passenger travel time. The proposed express-local mode establishes stable tracking relationships within train pairs, ensuring effective RBE utilization. Comparative analyses reveal that deadheading is more effective than flexible skip-stop for energy-efficient and time-saving metro operations.

Energy Harvesting Technologies in Electric Vehicles and Applications in Sustainable Agricultural Transportation: A Review

The increasing challenges of energy depletion, environmental pollution, climate change, and agricultural transportation costs demand innovative solutions. Electric vehicles (EVs) offer a promising solution towards mitigating these issues through renewable energy sources. However, limited driving range remains a crucial barrier to their widespread adoption, particularly in environmentally friendly agricultural transportation. This review paper comprehensively analyzes energy harvesting technologies in electric vehicles and their application in agricultural transportation. The focus is on their potential to improve driving range and address the specific needs of farmers in terms of maximizing their income. Very few review articles have been published on maximum number of possibilities of harvesting energies in electric vehicles, application in agricultural transportation and future prospects for improvement. Existing and current literature was systematically reviewed on various energy harvesting techniques applicable to EVs, including solar energy harvesting, regenerative braking, aerodynamic (wind) energy recovery, and vibration energy harvesting through suspension systems which are all renewable energy sources. Their advantages, working principle, limitations, and recent advancements were critically discussed. All explored energy harvesting methods show the ability to extend EV driving range. However, solar energy and wind or aerodynamic energy harvesting in EVs are theoretically possible but still under research for practical applications due to lots of limitations. Regenerative braking and vibration energy harvesting show the most promising current applications. The Electrical or electromagnetic vibration energy harvesters produce better results over mechanical (hydraulic and pneumatic harvesters). When optimization is employed, better results were achieved. Research on the application of artificial intelligence based computer algorithms to optimize and produce the best amount of harvested energy in EVs will play a significant contribution in the adoption of EVs for sustainable agricultural transportation.

Optimal operation of co‐phase traction power supply system with HESS and PV

AbstractThe co‐phase traction power supply system (TPSS) with hybrid energy storage system (HESS) and photovoltaic (PV) is proposed to eliminate the neutral section and improve the regenerative braking energy (RBE) utilization. Although the integration of HESS and PV facilitates the energy saving and cost reduction of the co‐phase TPSS, the high cost and configuration of HESS should be considered, which is the key to affect the optimal operation strategy of co‐phase TPSS. Here, the optimal operation strategy of co‐phase TPSS with HESS and PV is proposed to design the HESS configuration, recycle RBE and improve power quality. The proposed model aims to minimize the total system cost, including HESS investment cost, electricity cost and operation and maintenance cost. Moreover, the proposed model is formulated as a mixed integer linear programming by employing linearization approaches. Finally, case studies verify that the 29.2% cost reduction rate is achieved and the three‐phase voltage unbalance meets the standard requirements.

Modeling and SOC estimation of on-board energy storage device for trains under emergency traction

The sudden interruption of train power supply in an extreme environment will seriously threaten the safety of passengers and affect the operational efficiency of the railway system. In this case, the focus of attention becomes a method of running the train to the nearest rescue point based on the limited capacity of the on-board emergency energy storage device. Therefore, this paper reports research on the state of charge (SOC) estimation of train energy storage equipment to optimize the emergency traction strategy and energy utilization rate of trains to the maximum extent. First, with the emergency power supply of on-board lithium titanate batteries, the energy flow model of train emergency power supply is constructed for the first time. Second, based on the second-order equivalent circuit model and considering the utilization of regenerative braking energy, the relationship between battery capacity and open circuit voltage (OCV), temperature, current and SOC are constructed through experimental data, which significantly improves the accuracy and robustness of SOC estimation in complex and variable environments. Then, to effectively eliminate the impact of environmental on the estimation especially in the case of extremely low temperature (−20 °C), online model parameter discrimination and SOC estimation of lithium batteries are realized by combining recursive least squares with an optimal forgetting factor (FRLS) algorithm and a new temperature forgetting factor based adaptive extended Kalman filter (TFFAEKF) algorithm. The experimental results show that the proposed method achieves accurate SOC estimation, and the maximum error is less than 1% at different temperatures.

Multi-objective online driving strategy optimization for energy storage tram considering battery life

Compared with the traditional overhead contact grid or third-rail power supply, energy storage trams equipped with lithium batteries have been developed rapidly because of their advantages of flexible railway laying and high regenerative braking energy utilization. However, trams may face expensive battery replacement costs due to battery degradation. Therefore, this paper proposes a multi-objective optimization method for the tram's driving strategy to reduce operational energy consumption and extend battery life. The method describes the optimization problem as second-order cone programming (SOCP). It uses the interior point algorithm for fast solving, thus obtaining the theoretical optimal speed trajectory in real-time. This feature enables the method to be applied online. To verify the effectiveness and robustness of the proposed method, we conducted simulations under actual operating conditions. The simulation results show that the proposed multi-objective optimization method can extend the battery life by 40 % compared to the single-objective optimization method for energy saving. As a result, the total cost of the whole life cycle is reduced by 6.54 %. Furthermore, this online optimization driving strategy method can effectively deal with unexpected conditions during the actual operation of the tram to ensure the secure operation, punctual arrival, and precise parking of trams. Finally, the effectiveness of the proposed method is further verified by a hardware-in-the-loop (HIL) test.

Downshifting strategy of plug-in hybrid vehicle during braking process for greater regenerative energy

The P2 configuration plug-in hybrid electric vehicle (P2-PHEV) equipped with a multi-speed transmission has a high potential for recovering more regenerative energy, as the shifting strategy can be employed to adjust the working zone of the electric motor (EM). However, the existing shifting strategy designed for normal driving conditions cannot achieve optimal regenerative energy recovery. In this study, a shifting strategy used in the regenerative braking process is proposed. First, to make the EM provide more regenerative force during braking, a braking force distribution algorithm is devised while simultaneously considering braking stability and safety. Second, to realize maximum regenerative braking energy recovery, an optimal shifting strategy is designed for regenerative braking. Third, the classical braking process is analyzed and six thresholds are abstracted and optimized to establish a rule for restraining frequent gearshifts raised in the proposed optimal shifting strategy. Finally, the proposed strategy is verified under three standard cycles, results show that the proposed shifting strategy can recover considerable regenerative energy without frequent gearshifts.

Energy recovery in automotive systems: A review of regenerative braking, flywheel, thermoelectric, rankin cycle and electric turbo compound

In the backdrop of escalating global vehicle proliferation and the consequent surge in carbon dioxide (CO2) emissions, there is a compelling urgency to innovate energy recovery methods during vehicular operations for heightened energy efficiency and substantial environmental emission reductions. This paper discussed a variety of vehicle technologies to address environmental emissions issues and critically evaluates contemporary energy recovery technologies across three core dimensions: automotive thermal energy conversion, electronic turbine systems (ETC), and kinetic energy recovery systems. By analyzing empirical data encompassing CO2 emission reduction, energy recovery efficiency enhancement, fuel economy improvement, and applicability diversity across vehicle models, the study aims to establish a scientific foundation for continuous vehicular energy efficiency enhancement and emission reduction. This entails a comprehensive investigation of internal combustion engine principles for potential heat energy recovery, juxtaposing conventional and advanced cycles like the Rankine cycle. Moreover, it involves assessing ETC effectiveness in utilizing exhaust energy while acknowledging system complexity and dynamic response challenges. Additionally, the performance disparities of kinetic energy recovery systems like regenerative braking and exhaust energy recovery in distinct operational contexts are examined. By meticulously comparing experimental data, the paper intends to provide a comprehensive assessment of each technologys merits and drawbacks in advancing energy efficiency and emission reduction, try to pick one or more combinations to minimise the impact, thereby guiding future research and application in automotive energy recovery, and contributing to sustainable automotive engineering technology advancement.

Power Flow Control-Based Regenerative Braking Energy Utilization in AC Electrified Railways: Review and Future Trends

Power Flow Control-Based Regenerative Braking Energy Utilization in AC Electrified Railways: Review and Future Trends

A novel stochastic framework for optimal scheduling of smart cities as an energy hub

AbstractSmart cities consist of various energy systems and services that must be optimally scheduled to improve energy efficiency and reduce operation costs. The smart city layout comprises a power distribution system, a thermal energy system, a water system, and the private and public transportation systems. Additionally, several new technologies such as reconfiguration, regenerative braking energy of the metro, etc. are considered. This study is one of the first to consider all these technologies together in a smart city. The proposed power distribution system is a grid‐connected hybrid AC–DC microgrid. The biogeography‐based optimization algorithm was utilized to seek the best solution for scheduling micro‐turbines, fuel cells, heat pumps, desalination units, energy storage systems, AC–DC converters, purchasing power from the upstream, distributed energy resources, and transferring power amongst electric vehicle parking stations and metro for the next day. Also, the reduced unscented transformation layout was used to capture the system's uncertainty. The suggested layout is implemented on an enhanced IEEE 33‐bus test system to show the efficiency of the suggested method. The results show that costs and environmental pollution are reduced. By comparing the proposed smart city with other studies, the efficiency and completeness of the proposed smart city are shown.

Modelling a DC Electric Railway System and Determining the Optimal Location of Wayside Energy Storage Systems for Enhancing Energy Efficiency and Energy Management

Global demand for fossil fuels is highly increasing, necessitating energy efficiency to be enhanced in transitioning to low-carbon energy systems. Electric railways are highly efficient in reducing the transportation demand for fossil fuels as they are lightweight and their energy demand can be fed by renewable energy resources. Further, the regenerative braking energy of decelerating trains can be fed to accelerating trains and stored in onboard energy storage systems (ESSs) and stationary ESSs. It is fundamental to model electric railways accurately before investigating approaches to enhancing their energy efficiency. However, electric railways are challenging to model as they are nonlinear, resulting from the rectifier substations, overvoltage protection circuits, and the unpredictability and uncertainty of the load according to the train position. There have been few studies that have examined the ESS location’s impact on improving the energy efficiency of electric railways while using specialised simulation tools in electric railways. However, no single study exists that has studied the location impact of stationary ESSs on the energy efficiency of electric railways while the trains are supported by onboard ESSs. Given these goals and challenges, the main objective of this work is to develop a model using commercial software used by industry practitioners. Further, the energy saving is aimed to be maximised using stationary ESSs installed in optimal locations while trains are supported by onboard ESSs. The model includes trains, onboard ESSs, rail tracks, passenger stations, stationary ESSs, and traction power systems involving power lines, connectors, switches, sectioning, and isolators. In this article, a test scenario is presented comprising two trains running on a 20 km with three passenger stations and two substations. The trains and track are modelled in OpenTrack simulation software (Version 1.9) while the power system is modelled in OpenPowerNet simulation software (Version 1.11). The two simulation tools are used in the railway industry and can produce realistic results by taking into account the entire electrical network structure. A stationary ESS is added on the wayside and moved in steps of 1 km to obtain the optimal location before investigating the impact of stationary ESSs on the performance and energy management of onboard ESSs. It is found that the energy saving when installing a stationary ESS at the optimal location is 56.05%, the peak-power reduction of Substation 1 is 4.37%, and the peak-power reduction of Substation 2 is 18.67%.

Power Sharing and Storage-Based Regenerative Braking Energy Utilization for Sectioning Post in Electrified Railways

Power Sharing and Storage-Based Regenerative Braking Energy Utilization for Sectioning Post in Electrified Railways

Investigations of Regenerative Braking and Vibration Energy Conservation for Efficient Charging of Lithium-Ion Battery and Supercapacitor Hybrid System in Electric Vehicle Applications

This study aims to determine new methods of making electric vehicles more energy efficient by focusing on regenerative braking and vibration energy conservation in a hybrid energy storage system integrating lithium-ion batteries and supercapacitors. The first part of the research identifies the regenerative braking system, evaluates its effectiveness, and proposes enhancements for capturing and storing braking energy. Additionally, an investigation is made into whether it would be possible to conserve vibrating energies through creative integration with energetic harvesting technologies. The purpose is to capture and convert vibrational power produced when a car moves into an electrical charge using piezoelectric device for hybrid power storage. More energy efficiency is achieved through this method while also trying to overcome the shortcomings of regenerative braking in some driving situations. This experiments involve Modeling, Simulation and development and testing of prototype systems under different driving and vibrating conditions as well as real-world performance evaluation. It will help to determine how effective the hybrid system that has been suggested enhances energy recovery and storage efficiency in electric vehicles.

Metro timetable optimization for improving regenerative braking energy utilization efficiency

The train generates regenerative braking energy (RBE) during braking. When the RBE generated by the braking train is too large to be absorbed and utilized, the OCS voltage will rise rapidly. It may even exceed the rated voltage threshold, resulting in hidden dangers for driving safety. How to use RBE efficiently and reasonably has become a hot issue in recent years. This paper presents a metro timetable optimization method for multi-train operation to improve the RBE utilization efficiency of trains. Firstly, an energy-saving multi-objective model for multi-train operation is established, which takes the total energy consumption and travel time as the objective functions and the dwell time and departure interval as the constraints. Then, the genetic algorithm (GA) is used to generate the composition sequence of dwell time and departure interval, and the multi-node nonlinear model is used to calculate the total energy consumption of the metro line. Finally, Guangzhou metro line 7 is selected as an example to illustrate the effectiveness of the developed optimization model. The results show that the energy consumption of the whole line can be effectively reduced by adjusting the dwell time and departure interval. Meanwhile, the timetable optimization model with GA has better energy-saving effects by comparative analysis.

Design of Regenerative Braking System and Energy Storage with Supercapacitors as Energy Buffers

Vehicles are part of urban area transport and are subjected to variable loads as they traverse the city with varying slopes and stop-and-go traffic. Electric Vehicles (EVs) can be a good option because of their high efficiency under stop-and-go conditions and ability to gain energy from braking. However, limited battery energy makes EVs less efficient and degrades their lifetime. In contrast to a Li-Ion battery, supercapacitors work well under high power charge and discharge cycles. However, their high cost and low energy density prevent them from being viable replacements for batteries. Due to the slow charging and discharging process of batteries, they have a low power density, but a high energy density compared to the supercapacitor. In this paper, we discussed our system design consisting of both a battery and a supercapacitor. The main aim is to design and develop a scheduling algorithm to optimize energy flow between the battery, supercapacitor, and motor. We further described an analogue-based control methodology and algorithm for the supercapacitor, augmented battery-powered motoring process. This is in addition to a charge controller designed to optimize the supercapacitor bank's current-based charge-discharge profile. The system design and tests are developed on PSPICE and a hardware platform.

Coordinated control strategy of electro-mechanical composite braking for four-wheel drive electric vehicles

Regenerative braking energy recovery technology is critical for electric vehicles, which can significantly improve vehicle mileage. In addition, the regenerative braking system is often used with the friction braking system to provide vehicle braking force. This paper presents an electro-mechanical compound brake control strategy for four-wheel drive electric vehicles equipped with an electro-mechanical braking system. Firstly, the configuration of a four-wheel drive electric vehicle with an electro-mechanical braking system is introduced. The mathematical models of the driving motor, battery, and electro-mechanical braking are established. Secondly, a new control method is introduced by optimizing torque allocation based on maximum energy recovery with considering battery limits and a cooperative control method of the electro-mechanical composite braking system. It can be ensured that the braking energy recovery capability and braking comfort. Finally, simulation results indicate that the introduced control strategy can increase the braking recovered energy by 3% and 4%, respectively, under NEDC and WLTC conditions, compared to the ideal braking force distribution strategy. The introduced control method can effectively decrease the braking impact and ensure braking comfort in the coordination control section.

Cooperative Application of Onboard Energy Storage and Stationary Energy Storage in Rail Transit Based on Genetic Algorithm

The transition towards environmentally friendly transportation solutions has prompted a focused exploration of energy-saving technologies within railway transit systems. Energy Storage Systems (ESS) in railway transit for Regenerative Braking Energy (RBE) recovery has gained prominence in pursuing sustainable transportation solutions. To achieve the dual-objective optimization of energy saving and investment, this paper proposes the collaborative operation of Onboard Energy-Storage Systems (OESS) and Stationary Energy-Storage Systems (SESS). In the meantime, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to optimize the ESS capacity and reduce its redundancy. The simulation is programmed in MATLAB. The results show that the corporation of OESS and SESS offers superior benefits (70 kWh energy saving within 30 min operation) compared to using SESS alone. Moreover, the OESS plays a significant role, emphasizing its significance in saving energy and investment, therefore presenting a win–win scenario. It is recommended that the capacity of OESS be designed to be two to three times that of SESS. The findings contribute to the ongoing efforts in developing more sustainable and energy-efficient transportation solutions, with implications for the railway industry’s investment and broader initiatives in energy saving for sustainable urban mobility.

Regenerative Braking Energy Utilization Analysis in AC/DC Railway Power Supply System With Energy Feedback Systems

In the power supply system with energy feedback system (EFS)s, the energy from EFS (WF) will flow to rectifiers, which is circulation flow (CF). However, the efficiency of CF between substations has been rarely studied. Besides, the relationship between the train operation and regenerative braking energy (RBE) utilizing efficiency is not clear. In this paper, the energy flow structure of the AC/DC railway power supply system including CF is established. In the double-train system, promoting CF when the trains’ distance is long can be beneficial to power utilization efficiency. Chengdu Metro Line 9 is analyzed as the multi-train system based on the iterative AC/DC power flow algorithm. The key to energy saving includes reducing the energy consumption of on-board resistance and the DC traction network loss. Compared with the catenary and rail system, the fourth-rail system can promote system energy efficiency by 23.5% at most. The CF and energy fed to main substations counts for less than 2% and 8% of WF. When the headway time is short, RBE should be avoided feedback to EFS, while the feedback power of EFS should be advocated when the headway time is long. The results can help guide the operation of urban rail to save energy.

Analysis and Control of Cascaded Energy Storage System for Energy Efficiency and Power Quality Improvement in Electrified Railways

Energy-efficient and grid-friendly railway power system is critical for the sustainable development of electrified railways. In this paper, a cascaded energy storage system (CESS) is investigated for energy efficiency and power quality improvement of the railway power system. First, the detailed operation principles of the CESS for multiple control objectives, including regenerative braking energy (RBE) utilization, reactive power compensation, and negative sequence current suppression, are analyzed. On this basis, a hierarchical power flow control strategy is developed for achieving the power flow management and control of multiple objectives for CESS. Specifically, a multi-objective power flow management strategy is designed in the system layer to allocate the power references for the CESS under sufficient and insufficient capacity scenarios. In the sufficient capacity scenario, the power references are directly obtained by the operation principles. In the insufficient capacity scenario, the power references are allocated through a three-stage optimization method considering the power shaving rate, grid power factor, and grid imbalance degree. Subsequently, the power references from the system layer are tracked in the converter layer to achieve power flow control. Finally, the effectiveness of the proposed hierarchical power flow control strategy is verified through experimental results. The results show that the proposed CESS can achieve superior performance on RBE utilization and power quality improvement under complex operating conditions in electrified railways.

Urban Rail System Modeling and Simulation Based on Dynamic Train Density

To further improve the simulation calculation ability of urban rail traction systems during the peak operation period and provide an accurate and reliable simulation tool for the subsequent train schedule and energy storage system design, a multi-train circuit model with a bilateral power supply was established in this paper, and a power calculation algorithm based on dynamic train density was designed. The circuit topology in the model can be dynamically adjusted according to the number of trains to improve the operation rate. Based on the spatial and electrical data of a real section of the subway, the urban rail circuit model was built on the MATLAB platform, and the actual operation data of the subway was imported for verification. The experimental results show that the multi-train model can accurately reflect the influence of voltage fluctuations on the traction system under different train running conditions, and the results fit the actual operation conditions. By comparing the influence of different train intervals on the RBE (regenerative braking energy) utilization, the results show that the optimal RBE utilization rate can be achieved by adjusting the train interval in the peak period.