Braking Energy Research Articles

A Multifunctional Energy Storage System With Fault-Tolerance and Its Hierarchical Optimization Control in AC-Fed Railways

To better recycle the regenerative braking energy (RBE) and improve the power quality (PQ) in asymmetric AC-fed railways, a novel multiplex back-to-back energy storage system (MB2ESS) with fault-tolerance ability is proposed, where individual subsystems not only independently operate as self-controlled entities, but also collaborate with adjacent subsystems to resist system disturbances and local faults. On this basis, a hierarchical optimization control method with three-layer structure is designed for the flexible and effective operation of MB2ESS, including the global optimization layer based on finite state machine, the regional decision-making layer with event-driven distributed coordination controller, and the local execution layer via multi-converter autonomous control. It can be used to seamlessly switch different operation modes, coordinately manage the multidirectional transmission of RBE, dynamically control PQ optimization compensation, and rapidly perform fault response behaviors. Subsequently, through typical scenarios, comparative study, and field case of a traction substation in Beijing-Shanghai Railway, the feasibility and effectiveness of proposed scheme are verified. The engineering capability assessment results also show that this scheme can effectively make up for the structure and function deficiencies of conventional railway energy storage systems, which has well adaptability and application potential.

Joint optimization combining the capacity of subway on‐board energy storage device and timetable

On-board energy storage devices (OESD) and energy-efficient train timetabling (EETT) are considered two effective ways to improve the usage rate of regenerative braking energy (RBE) of subway trains. EETT is less costly but has lower ceilings, whereas OESD, although expensive, maximizes the reuse of RBE. To make the RBE usage rate of the train group reach the required target, a typical problem is how to use the OESD with the minimum capacity to reduce the cost. With this consideration, this paper proposes an optimization method that combines EETT and OESD. In this method, the joint optimization of timetable and OESD capacity allocation in case OESDs of different capacities can be carried between trains is considered to further improve the optimization. A non-linear programming model is built to minimize the total OESD capacity of the train group under the constraint of reaching target RBE usage. An efficient heuristic algorithm is designed to simultaneously obtain the optimal timetable and the matching capacity allocation scheme of OESDs. Finally, some simulation cases based on real-line data are designed to verify the effectiveness of the method.

Study on Speed Planning of Signalized Intersections with Autonomous Vehicles Considering Regenerative Braking

In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with roadside facilities and regional central control. Our objectives were as follows; firstly, to establish the simulation model of the hybrid energy regenerative braking system (HERBS) and to verify it by bench test. Secondly, to build up the genetic algorithm (GA) optimization model for the deceleration stopping of the HERBS. Then, to obtain signal light status and timing information to be the constraints; the BERE is to be the optimized objective, resulting in optimization for the speed trajectory under the deceleration stopping condition of a single signalized intersection. Finally, vehicle simulations in ADVISOR software are utilized to validate the optimization results. The results show that the BERE during deceleration stopping at a single signalized intersection after the speed trajectory optimization is 36.21% higher than that of inexperienced drivers, and 7.82% higher than that of experienced drivers.

Optimal linearized operation of electric railway system in the presence of flexible renewable sources and switchable capacitor banks considering supply and demand sides’ uncertainties

The electric train (ET) is a great energy consumer in an electrical network, which regenerates a high amount of energy into the grid at the braking moment. Therefore, in this paper, the optimal operation of the electric railway system is proposed considering renewable sources, hybrid storage systems (battery and ultracapacitor units), switchable capacitor banks, and regenerative braking energy of ET at the same time to attain a favorable economic, environmental and operational condition. Renewable sources reduce operating costs and environmental pollution. The storage system is utilized as a flexible source along with renewable generations. The ultracapacitor stores the ET braking energy, and the capacitor bank regulates the voltage. The scheme minimizes the expected network operating cost, while the AC optimal power flow and other technical limits are considered. This problem is nonlinear, and a linearized approximation formulation is implemented to achieve a unique optimal solution with the best and minimum computation time. The unscented transformation method is used to model uncertainties of load, ETs’ energy consumption, and renewable energies. Finally, by evaluating the numerical results, it is illustrated that the efficiency of the proposed method simultaneously improves the economic, environmental, and operational features of the network.

Reduction of vehicle exhaust gas toxicity due to brake energy recovery

BACKGROUND: In recent years, fleet of vehicles in the Russian Federation is on a significant increase, that leads to considerably amplified emissions of toxic gases into the atmosphere. The share of toxic gas emissions from motor vehicles ranges from 65 to 70%. In order to reduce the toxic gas emissions into the atmosphere, electric vehicles have been introduced, but they have a number of disadvantages. These are a limited mileage before recharging and expensive batteries. Also, works on the use of hydrogen as a fuel for cars are conducted at an accelerated pace. However, the issue of a hydrogen fuel storage has not yet been worked out. At the same time, the used fleet of vehicles continues to poison the atmosphere.
 AIMS: Studying the braking energy recuperator for decreasing carbonic oxide CO in exhaust gases of the UAZ car.
 METHODS: The construction of a combined unit with a gas-hydraulic braking recuperator was developed, which is installed on a UAZ vehicle (RF Pat. No. 2193977). Comparative studies were carried out in accordance with GOST 33670-2015 and GOST 52033-2003.
 RESULTS: Results of comparative studies of the car showed that a minimum of CO emissions is observed in high gear, at a speed of 1825 m/s, and CO emissions significantly increase in lower gears. The recuperator eliminates this drawback due to the additional power transmission to the driving wheels.
 CONCLUSION. When a car starts in the urban cycle, there is a minimum of CO emissions with a recuperator, at the same time the car acceleration increases, that reduces the acceleration time and the distance by 3035%. A car with a recuperator on average consumed gasoline up to 15 l per 100 km, and this parameter of the production car was up to 17,5 l per 100 km of track. Due to the recuperator, CO emissions are reduced by 16%.

Timetable Optimization and Trial Test for Regenerative Braking Energy Utilization in Rapid Transit Systems

Rapid transit systems play a significant role in supporting rapid social and economic development in large cities all over the world. However, the systems consume a large amount of energy, which brings increasing environmental concerns. A number of energy-saving technologies have been studied on railways. However, few of the outcomes have been tested and evaluated in practice. This paper presents the development of a timetable optimization and trial test on a metro line to reach the full potential of the train regenerative braking system. To achieve this purpose, a timetable optimization algorithm has been developed, and a trial test of the optimal timetable has been arranged on a metro line for a whole day. In the test, all the trains running in the network were organized to operate in accordance with the optimal timetable. The trial test results indicate that by applying the optimal timetable, the regenerative braking energy utilization can be improved, thereby reducing the overall network energy usage.

Energy Management Strategy for Fuel Cell/Battery/Ultracapacitor Hybrid Electric Vehicles Using Deep Reinforcement Learning With Action Trimming

As for fuel cell hybrid electric vehicle equipped with battery (BAT) and ultracapacitor (UC), its dynamic topology structure is complex and different characteristics of three power sources induce challenges in energy management for fuel economy, power sources lifespan, and dynamic performance of the vehicle. In this paper, an energy management strategy (EMS) based on a hierarchical power splitting structure and deep reinforcement learning (DRL) is proposed. In the higher layer strategy of the proposed EMS, the UC is employed to supply peak power and recover braking energy through the adaptive filter based on fuzzy control. Then, the integrated DRL and equivalent consumption minimization strategy framework is proposed to optimize the power allocation of fuel cell (FC) and BAT in the lower layer, to ensure the highly efficient operation of FC and reduce hydrogen consumption. And the action trimming based on heuristic technique is proposed to further restrain the adverse effect of sudden peak power on FC lifespan. The simulation results show the proposed EMS can make the output of FC smoother, improve its working efficiency to alleviate the stress of BAT, and increase by 14.8% compared with the Q-learning strategy in fuel economy under WLTP driving cycle. Meanwhile, the obtained results under UDDSHDV show fuel economy of the proposed EMS can reach dynamic programming (DP) benchmark level of 89.7 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Integrated Rail System and EV Parking Lot Operation With Regenerative Braking Energy, Energy Storage System and PV Availability

A significant advancement regarding the electrification of transportation has occurred in recent years due to technological developments, environmental concerns, and geopolitical issues in the energy areas all over the world. In this study, a new concept for the integration of rail-based public transportation systems with electric vehicle (EV) parking lots operated by a “park and ride” strategy is propounded, including also renewable resources based energy production. In the proposed structure, the charging power demand of the EV parking lot is supplied by different charging strategies considering the existing unused energy infrastructure capacity and the regenerative braking energy of the railway system, altogether. Here, the design of a photovoltaic (PV) based carport type renewable energy production unit is also realized in the existing local parking area. The development of an optimal energy management system to effectively manage these inputs is realized and the uncertainties pertaining to EVs’ demand are also taken into account. To demonstrate its efficacy, the concept is tested considering a bench of case studies and comprehensive results are obtained.

Research on Braking Energy Recovery by Accumulator of Hybrid Electric Vehicle

Research on Braking Energy Recovery by Accumulator of Hybrid Electric Vehicle

Optimal Control Strategy of Path Tracking and Braking Energy Recovery for New Energy Vehicles

In order to further improve the stability of path tracking control and fuel economy of new energy vehicles, an optimal control strategy of path tracking and braking energy recovery is proposed. First, a model predictive controller is designed based on the three-degrees of freedom dynamics model of the vehicle according to the idea of hierarchical control, and a fuzzy yaw torque controller is established with the desired yaw velocity and side slip angle of the mass center as constraints. Second, at high-speed driving conditions, the executive layer of the component distributes the braking torque according to the braking energy recovery control strategy. Finally, the optimal control strategy of path tracking and braking energy recovery is verified by Carsim/Advisor/Simulink software under different driving speeds. The results show that the optimized control strategy can improve the tracking accuracy and driving stability of a vehicle with large curvature turning and further improve the fuel economy of new energy vehicles under the premise of meeting the control requirements.

Two Generations of Hydrogen Powertrain—An Analysis of the Operational Indicators in Real Driving Conditions (RDC)

Hydrogen fuel cells are systems that can be successfully used to partially replace internal combustion propulsion systems. For this reason, the article presents an operational analysis of energy flow along with an analysis of individual energy transmission systems. Two generations of the Toyota Mirai vehicle were used for the tests. The operational analyses were carried out on the same route (compliant with RDE test requirements), assessing the system’s operation in three driving sections (urban, rural and motorway). Both generations of the drive system with fuel cells are quite different, which affects the obtained individual systems operation results as well as the overall energy flow. Research was carried out on the energy flow in the fuel cells, FC converter, battery and electric motor using a dedicated data acquisition system. The analyses were carried out in relation to the energy of fuel cells, battery energy and recovered braking energy. It was found that in the urban drive section of the second-generation system (due to its much larger mass), a slightly higher energy consumption value was obtained (by about 2%). However, in the remaining phases of the test, consumption was lower (the maximum difference was 18% in the rural phase). Total energy consumption in the research test was 19.64 kWh/100 km for the first-generation system compared to 18.53 kWh/100 km for the second-generation system. Taking into account the increased mass of the second-generation vehicle resulted in significantly greater benefits in the second-generation drive (up to 37% in individual drive sections and about 28% in the entire drive test).

Research on Braking Efficiency of Master-Slave Electro-Hydraulic Hybrid Electric Vehicle

To address the problems of short-rangee and poor braking safety of electric vehicles, this paper proposes a master-slave electro-hydraulic hybrid passenger car drive system based on planetary gear. The system couples the electrical energy output from the electric motor with the hydraulic energy output from the electro-hydraulic pump/motor through the planetary gear. The hydraulic system is used as the auxiliary power source of the power system giving full play to the advantages of the hydraulic system and the electric system. After theoretical analysis, this paper establishes a master-slave electro-hydraulic hybrid electric vehicle (MSEHH-EV) model based on planetary gear in AMESim software. A braking energy recovery control strategy is designed with the maximum braking energy recovery efficiency as the target. Braking strength determines the switching of braking modes. Finally, comparing the certified pure electric vehicle (EV) model in AMESim, we are able to substantiate the superiority of the strategy proposed in this paper. The simulation results revealed that the battery consumption rate of the new power vehicle is reduced by 17.766%, 11.358%, and 9.427% under UDDS, NEDC, and WLTC conditions, respectively, which supports the range. At the same time, the braking distance is significantly shortened, and the maximum braking distance is shortened by 15.65 m, 21.97 m, and 21.45 m, respectively, under the three operating conditions, which improves the braking safety.

Electrical power supply system planning for a modern catenary-free rapid charging

Electric power supply system planning is practically an important function of the modern light rail transit system with catenary free operation and rapid charging. Installing a modern dynamic load of the traction power supply system with the local electric distribution network needs to consider its capacity and feeder to support enough and efficiently. In this paper, the design of the electrical power supply system of the pilot project of Nakhon Ratchasima Green Line light rail system with 11.6-km line length and 21 passenger stations operated with catenary-free and powered with an on-board energy storage device has been proposed and planned to replace the old local transportation. The traction power supply of the light rail system drawn power from the MV distribution feeder practically consist of receiving power substation, MV power feeding system power feeder substation, charging power supply and service power supply have been designed provided the configuration circuit. A rapid charge system to delivery high power to fulfill the on-board energy storage is considered to recharge at passenger stations with an overhead conductor or wireless power transfer during a short dwell time. A number of charging station is determined accordingly the capacity of the power substation and its positions. The traction power drawn by a train service round-trip that related to the capacity of the power substation as a charging station has been calculated by the simulation of the train movement. The regenerative braking energy during train operated in braking mode is also considered as a partial charging energy the on-board energy storage device. From the proposed design, the motive energy consumption of each scenario charging formations obtains the maximum charging energy drawn by the train between charging points, the capacity of on-board energy storage devices, maximum charging power and the total charging points.

Energy management strategy for hydraulic hybrid system with compound accumulator based on dynamic programming

The compound accumulator is an energy storage device composed of one large accumulator and one small accumulator. Compared with traditional single-accumulator hydraulic hybrid vehicles, hydraulic hybrid vehicles based on compound accumulator can switch the working timing of large and small accumulators according to the characteristics of different working conditions, more braking energy can be recovered on the premise of providing enough braking strength. This article is aimed at hydraulic hybrid vehicles based on compound accumulator. First, the key components of the hydraulic system were matched, then according to the engine fuel consumption curve, the engine’s high-efficiency work area is divided, and formulated a rule-based energy management strategy based on the principle of adjusting the engine to work in a high-efficiency area. The internal pressure of the compound accumulator is selected as the state variable, the ratio of the torque of the hydraulic pump/motor to the required torque of the vehicle is the control variable, and the optimal fuel economy of the entire cycle is the objective function, and the mathematical model is established using the dynamic programming algorithm, and compiled a program in MATLAB to obtain the optimal torque distribution relationship between the engine and the hydraulic pump/motor and the optimal working timing of the large and small accumulators. Simulation results show that compared with the traditional hydraulic hybrid vehicle with single accumulator based on initial rules and the hydraulic hybrid vehicle with compound accumulator based on initial rules, the hybrid vehicle with compound accumulator based on improved rules can save fuel by 11.84[Formula: see text] and 5.96[Formula: see text] respectively. The fuel saving potential of the compound accumulator structure and the effectiveness of the improved rule control strategy based on dynamic programming algorithm are verified.

Easy-to-implement measurement method for the energy dissipated on board train with uncertainty estimation

In the near future, the railway is seen as the most important solution for reducing greenhouse gas emissions due to transportation. Investment in this sectors are ongoing, in order to increase both the level of service and energy efficiency. The adoption of recent technological solutions, as storage systems or reversible substations, could foster the efficiency, increasing the capability of recovering braking energy. The braking energy is very difficult to measure, it requires installing expensive measurement systems on board trains. In a previous paper the authors already faced this issue developing an accurate technique usable off-line. In the present paper a simplified method, easy to be implemented on train control unit, based only on already available data, is proposed. The paper describes the phenomena of interest and related measurement issues. The analytical model for the power measurement together with a deep analysis on the input quantities are presented. The uncertainty analysis of the proposed method is presented and the uncertainty budget is performed on a real test case. The metrological performances of the method show suitable accuracy level for train energy management.

Control strategy for high speed flywheel energy storage system based on voltage threshold of DC1500 V transit transportation traction grid

Energy storage equipment can play a unique advantage to recycle the regenerative braking energy of metro, of which flywheel energy storage system (FESS) has a good application prospect. At present, the control topology of FESS is two-level converter, and the DC voltage of FESS is mostly DC 750 V. High speed maglev-flywheel energy storage system (HSM-FESS) is used to recycle the braking energy in transit transportation. In order to achieve stable operation of the HSM-FESS, the control strategy based on the voltage threshold of the DC1500 V traction grid is adopted. At the same time, the Neutral Point Clamped (NPC) three-level control method of high speed maglev-permanent magnet motor (HSM-PMM) based on square wave modulation-two phase conduction (SWM-TPC) is proposed. A starting and braking simulation model of metro with HSM-FESS is built in MATLAB/Simulink, and the relevant simulation verification is completed.

Enhancing energy management of a stationary energy storage system in a DC electric railway using fuzzy logic control

In DC electric railways, energy storage systems (ESSs) have been addressed to assist in the energy efficiency improvement, which is achieved by exploiting the captured excess braking energy of decelerating trains in order to reduce the traction energy demand of the accelerating trains. Conventionally, stationary ESSs are assumed to have access to the substations and grid, which is being a significant shortcoming since the ESS in many locations such as the London Underground has neither access to the traction substations nor external sources. Since ESSs cannot have infinite capacity and have practical restrictions on the state of charge (SOC), much of the regenerative energies during braking are being lost, which reduces the benefits of ESSs in enhancing energy efficiency of electric railways. In this paper, boosting the energy efficiency of the system is achieved by proposing a new adaptive control method based on fuzzy logic control (FLC) to dynamically control a stationary ESS connected to a DC track system. Therefore, the power flow between the track and the ESS with respect to the storage capacity is managed without affecting the benefits yielded by the system. The proposed control method is simulated and tested experimentally on a real prototype including a supercapacitor ESS. Three traffic scenarios are applied to evaluate the feasibility and the performance of the proposed controller with respect to the undefined traffic scenarios matching the case in the London Underground. The proposed control method applied to three traffic scenarios have achieved energy savings of 39.2–41.4%. The experimental results are compared against the simulation results, showing a percentage error ranging from 1.8 to 3.6%.© 2017 Elsevier Inc. All rights reserved.

An Adaptive Energy Management Strategy of Stationary Hybrid Energy Storage System

In order to further improve the energy-saving and voltage stabilizing effect of the stationary energy storage system (ESS), this article tries to adopt the battery-supercapacitor (SC) hybrid ESS (HESS) as stationary ESS. The advantages of stationary HESS are verified by an example. An adaptive energy management framework for stationary HESS is proposed. A power distribution strategy is proposed to solve the adaptability of two energy storage media to the load variation of rail transportation power system, and to a certain extent, the battery degradation is delayed. The proposed strategy can not only realize the reasonable power-sharing between battery and SC considering the influence of headway on regenerative braking energy but also can keep the battery’s charge and discharge capacity for a long time by using fuzzy logic control (FLC). A simulation is carried out to illustrate the advantages of the proposed energy management strategy (PEMS). Finally, the PEMS is compared with two conventional strategies by the hardware-in-the-loop experiment platform, where it is shown to provide better performance (inferred through increases of 1.1% and 5.7% in energy conservation rate, 0.82% and 6.4% in voltage stabilization rate, and reduction of 2.26 and 0.36 A in the root-mean-square value of battery current at different headway).

Nonlinear Predictive Motion Control for Autonomous Mobile Robots Considering Active Fault-Tolerant Control and Regenerative Braking.

To further advance the performance and safety of autonomous mobile robots (AMRs), an integrated chassis control framework is proposed. In the longitudinal motion control module, a velocity-tracking controller was designed with the integrated feedforward and feedback control algorithm. Besides, the nonlinear model predictive control (NMPC) method was applied to the four-wheel steering (4WS) path-tracking controller design. To deal with the failure of key actuators, an active fault-tolerant control (AFTC) algorithm was designed by reallocating the driving or braking torques of the remaining normal actuators, and the weighted least squares (WLS) method was used for torque reallocation. The simulation results show that AMRs can advance driving stability and braking safety in the braking failure condition with the utilization of AFTC and recapture the braking energy during decelerations.

The Structure Principle and Dynamic Characteristics of Mechanical-Electric-Hydraulic Dynamic Coupling Drive System and Its Application in Electric Vehicle

To solve the problem of the low recovery rate of braking energy and the short driving range of electric vehicles, a novel mechanical-electric-hydraulic dynamic coupling drive system (MEH-DCDS) is proposed in this article. MEH-DCDS is a new power integration device that allows electric, mechanical, and hydraulic energy to be converted mutually. It comprises a swash plate plunger pump/motor and a permanent magnet synchronous motor. This article explains the structure and working principles of MEH-DCDS. We describe the dynamic characteristics of MEH-DCDS and analyze the pump and hydraulic motor in the MEH-DCDS hydraulic module. The simulation results show that the flow variation of the MEH-DCDS hydraulic module accords with the design concept of MEH-DCDS, and the pressure variation of high and low pressure accumulators also accords with the theoretical situation. The energy flow of Mechanical-Electric-Hydraulic Power Coupling Electric Vehicle (MEHPC-EV) under different working modes is expounded, and the mathematical model of its key components is established. Based on AMESim and Simulink, the article establishes a vehicle simulation dynamic model. The dynamic performance of MEHPC-EV in UDDS is analyzed by co-simulation. The simulation results show that the application of MEH-DCDS in electric vehicles is feasible. MEHPC-EV reduced battery energy consumption by 26.18% compared to EV. The research in this paper verifies the accuracy and superiority of the system, which has a significant reference value for the development and study of electric vehicles in the future.