Braking Energy Research Articles

Biomechanical Regenerative Braking Energy Harvester: A Systematic Analysis

Regenerative braking is a well-known technology applied in electric vehicles to achieve high energy efficiency through an energy-recovery mechanism. The same concept has been applied to robotic applications, such as legged robots, lower-limb prostheses, and biomechanical energy harvesters. In particular, a biomechanical energy harvester enables humans to generate watts of power while simultaneously assisting in the braking of human joints during walking. In this study, a systematic analysis of a biomechanical regenerative braking energy harvester was conducted. First, we reviewed the design considerations of each harvester component and designed an energy-harvester prototype with high power density through a systematic design process. Subsequently, the dynamics of the designed harvester and its effect on human biomechanics were analyzed through device testing and human testing. The designed harvester demonstrated a power density of 3.3 W/kg for level-ground walking during device testing. We evaluated muscle activities and joint kinematics in versatile walking scenarios such as sloped walking. In level-ground and downhill walking, the hamstring muscle activity was assisted by the braking torque simultaneously generating 1.2 W and 0.7 W, respectively, during negative work phase. Meanwhile, we confirmed that the braking torque was generated rather in the positive work phase interfering the quadriceps muscle activity. Comparing previous knee-joint-driven biomechanical regenerative braking energy harvesters, our harvester shows relatively high power density level even with slower walking speed and without any special mechanism.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40684-022-00472-6.

Estimating Brake Pad Life in Regenerative Braking Intensive Vehicle Applications

<div class="section abstract"><div class="htmlview paragraph">Regenerative braking without question greatly impacts brake pad service life in the field, in most cases extending it significantly. Estimating its impact precisely has not been an overriding concern - yet - due in part to the extensive sharing of brake components between regen-intensive battery-electric and hybrid vehicles, and their more friction-brake intensive internal combustion engine powered sibling. However, a multitude of factors are elevating the need for a more accurate estimation, including the emerging of dedicated electric vehicle architectures with opportunities for optimizing the friction brake design, a sharp focus on brake particulate emissions and the role of regenerative braking, a need to make design decisions for features such as corrosion protection for brake pad and pad slide components, and the emergence of driver-facing features such as Brake Pad Life Monitoring. Tackling this question raises questions such as “is the proven braking energy and temperature based wear model still sufficiently predictive of wear or do other mechanisms become dominant?”, and “how does customer behavior for charging and discharging of the battery affect brake pad life?” In the present study, validated models for brake pad life in the field are adapted for regenerative braking equipped vehicles, including simple models for the battery charge acceptance power, battery state of charge, electric drive unit characteristics, and customer battery charging habits. After correlating with field data, the models are used in case studies to illustrate some of the important considerations for friction brake wear on regenerative brake equipped vehicles.</div></div>

Modelling and Performance Analysis of Cyclic Hydro-Pneumatic Energy Storage System Considering the Thermodynamic Characteristics

The energy storage system of electric-drive heavy mining trucks takes on a critical significance in the characteristics including excellent load capacity, economy, and high efficiency. However, the existing battery-based system does not apply to harsh cold environments, which is the common working condition for the above trucks. A type of cycle hydro-pneumatic energy storage system for the trucks was proposed in this study. The dynamic model of the system, including the dynamic and thermodynamic models of hydraulic and pneumatic parts, was built to analyze the performance of the system. Subsequently, the thermodynamic characteristics were clarified during the energy storage and released through the real test condition-based simulation. The power and energy performances of the system were studied in practice based on the above characteristics. The analysis of the results showed that the system reduced 22.03% driving power at the optimal braking energy recovery rate, the energy density was nearly 12.6 MJ/m3, the maximum input power was higher than 230 kW, and the cycle efficiency was about 40.6%. The results of this study will be conducive to the application of the hydro-pneumatic energy storage system for the electric-drive mining trucks and reducing the resulting carbon emission.

JUSTIFICATION OF THE PARAMETERS OF THE PASSENGER CAR SERIES HYBRID POWER PLAN

The use of hybrid power plants in road transport can significantly improve driving dynamics and driving comfort, reduce its operating fuel consumption and emissions of harmful substances with exhaust gases. Due to the large number of used cars with internal combustion engines (ICE) in Ukraine, it is of interest to convert them into a hybrid power drive. However, the analysis of the literature revealed extremely limited information about the work in this direction. The paper proposes a method for selecting the parameters of elements of a series hybrid power drive based on a used Chevrolet Lacetti car. The technique is based on the use of mathematical models of the working process of the internal combustion engine, the dynamics of the acceleration of the car, the determination of the parameters of the series hybrid power plant in the modes of the European NEDC test cycle. Using the developed mathematical models, the rated power of the traction electric motor is 86 kW, the nominal and maximum rotational speed of its shaft, respectively, are 1860 and 7000 min-1. It is shown that the car will accelerate to 100 km/h in 11.4 seconds, which fully satisfies the conditions of comfortable driving in urban conditions. As part of a hybrid power plant, the internal combustion engine operates in one mode. The paper substantiates the choice of the operating mode of the internal combustion engine, where it has the best fuel efficiency. At the same time, its power is 34 kW, and the crankshaft speed is 2200 min-1. Accordingly, the power of the current generator will be 30 kW at a shaft speed of 2200 min-1. The paper analyzes the influence of the battery capacity, the presence of braking energy recuperation, the operating range of battery capacity change on the average operating fuel consumption of internal combustion engines. It is shown that an increase in the battery capacity, the presence of recuperation, and the expansion of the operating range of changes in the battery capacity lead to an improvement in the operational fuel efficiency of an internal combustion engine. Based on the results of computational studies, the maximum battery capacity of 1.3 kWh was selected; the operating range of capacity change was 0.8 kWh. The use of elements with such parameters will ensure the average operating fuel consumption of the internal combustion engine is 6.5 l/100 km, and with the recovery of braking energy - 6 l/100 km.

Energy Storage for High Speed Trains: Economical and Energy Saving Evaluation

Increasing the utilization rate of regenerative braking energy in rail systems is one of the ongoing applications increasing in significance in recent years. In rail systems, braking is made with two ways, mechanical and electrical. While the energy released due to mechanical braking cannot be recovered, the energy released due to electrical braking can be reused as regenerative braking energy. This regenerative braking energy varies according to the dynamics of the system and it can be given back to the grid, stored in storage devices or burned in resistors (it is not desired). This study develops a novelty algorithm within the scope of this objective and provides the calculation of the regenerative braking energy recovery rate and then making a decision for storage or back to grid of this energy. Afterwards, the regenerative braking energy was calculated with the help of this algorithm for Eskisehir-Ankara and Ankara-Eskisehir trips in two different passengers (load) scenarios, using the YHT 65000 high-speed train, which was chosen as a case study. Then, with a decision maker added to this classical regenerative braking energy algorithm, it will be decided whether this energy will be stored or forward back into the grid for the purpose of providing non-harmonic energy to the grid.

A Study on the Train Brake Position-Based Control Method for Regenerative Inverters

The use an inverter is one of the representative ways to utilize regenerative braking energy in railway systems. Due to the nature of urban railways that generate a large amount of regenerative energy, the economic advantages are clear. However, in the case of the existing inverter operation method, a method of operating the inverter using the threshold voltage is used, which has a disadvantage in that power cannot be utilized between the no-load voltage and the threshold voltage. Therefore, in this paper, we propose an optimal location selection method and capacity calculation method for installing a regenerative inverter in an urban rail system, and a control method according to the train brake position to increase the regenerative energy utilization rate. First, the inverter capacity and location were selected by selecting the maximum regenerative energy generation for each substation section through the train performance simulation (TPS) based DC power simulation (DCPS). An inverter control method based on train brake position (BP method) is introduced. Finally, PSCAD/EMTDC, a power analysis program, was used to verify the proposed method. As a result, the use of regenerative energy by an inverter increased by about 62.6%, and more energy was saved at nearby substations through the BP method.

Torque allocation strategy based on economy and stability for electric vehicle considering controllability after motors failure

To reduce the energy consumption and improve the stability of distributed drive electric vehicles, a torque allocation strategy based on an economy and stability optimisation function (ESOF) and a fuzzy proportional-integral-derivative rule control (FPRC) strategy are proposed while considering motor efficiency, braking energy recovery and motor failure. First, the vehicle dynamics and motor equivalent models are established. Subsequently, a torque prediction model and fuzzy controller for the vehicle are designed to calculate the total desired torque and yaw moment, respectively. A torque optimisation function is established to minimise power losses in the electric motor and maximise braking energy recovery, and it is solved using an improved genetic algorithm. While satisfying vehicle driving constraints, the ESOF-based controller can effectively coordinate the operation of each motor in the high-efficiency range under driving and braking conditions. After one motor fault is detected, the ESOF-based controller is replaced with an FPRC-based controller to distribute the vehicle demand torque. A co-simulation platform integrating MATLAB/Simulink and CarSim is developed to verify the effectiveness of the proposed ESOF-based controller in the New European Driving Cycle (NEDC) and Federal Test Procedure 75 (FTP75) driving cycles. The effectiveness of the FPRC-based controller in step steering condition is verified using the co-simulation platform. The simulation results indicate that the vehicle economy and driving range of the ESOF-based controller improved compared with the results afforded by the typical torque distribution strategy based on the front–rear axle dynamic load ratio. The average efficiencies of the motors in the NEDC and FTP75 driving cycles increased by 2.94% and 2.4%, respectively. More importantly, the FPRC-based controller can more significantly improve the steering stability of a vehicle with motor failure compared with the ESOF-based controller.

Strategy Design and Performance Analysis of an Electromechanical Flywheel Hybrid Scheme for Electric Vehicles

Energy management strategies are one of the key factors affecting the working efficiency of electric vehicle energy power systems. At present, electric vehicles will develop real-time and efficient energy management strategies according to the topology of on-board energy power system to improve the driving performance of vehicles. In this paper, a new electromechanical flywheel hybrid system is studied. Firstly, the characteristics of the topological scheme of the electromechanical flywheel hybrid system are analyzed, and the working modes are designed. Secondly, in order to improve the efficiency of vehicles’ energy utilization and ensure the real-time performance of the management strategy, an energy management strategy based on fuzzy rules is designed with the flywheel’s state of energy (SOE) as the key reference parameter. Then, considering the directional stability in the braking process, the braking force distribution strategy between the front axle and the rear axle is designed. In order to improve the braking energy recovery efficiency, the secondary distribution strategy consisting of a mechanical braking force and regenerative braking force on the front and rear axles is designed. Finally, the bench test of a electromechanical flywheel hybrid system is carried out. Experiments show that compared with the original dual-motor four-wheel drive scheme, the electromechanical flywheel hybrid four-wheel drive system scheme developed in this paper can reduce the current variation range of lithium batteries by 43.16%, increase the average efficiency by 1.04%, and increase the braking energy recovery rate by 40.61% under the Japan urban cycle conditions. In addition, taking advantage of the energy and power regulation advantages of the electromechanical flywheel device, the power consumption of the lithium battery is reduced by 1.82% under cycling conditions.

Deep reinforcement learning based energy management strategy for fuel cell/battery/supercapacitor powered electric vehicle

Vehicles using a single fuel cell as a power source often have problems such as slow response and inability to recover braking energy. Therefore, the current automobile market is mainly dominated by fuel cell hybrid vehicles. In this study, the fuel cell hybrid commercial vehicle is taken as the research object, and a fuel cell/battery/supercapacitor energy topology is proposed, and an energy management strategy based on a double-delay deep deterministic policy gradient is designed for this topological structure. This strategy takes fuel cell hydrogen consumption, fuel cell life loss, and battery life loss as the optimization goals, in which supercapacitors play the role of coordinating the power output of the fuel cell and the battery, providing more optimization ranges for the optimization of fuel cells and batteries. Compared with the deep deterministic policy gradient strategy (DDPG) and the nonlinear programming algorithm strategy, this strategy has reduced hydrogen consumption level, fuel cell loss level, and battery loss level, which greatly improves the economy and service life of the power system. The proposed EMS is based on the TD3 algorithm in deep reinforcement learning, and simultaneously optimizes a number of indicators, which is beneficial to prolong the service life of the power system.

Railway Alignment Optimization Considering Lifecycle Costs

The problem of railway alignment optimization is studied, with particular attention given to computing lifecycle costs while considering train speed profile optimization and traffic demand. Recurring expenses, including energy, user, and maintenance costs, are considered in the lifecycle. A novel speed profile optimization method for the energy-efficient operation of trains is developed and incorporated in a simulation model, which considers regenerative braking energy. According to the train motion simulation results, the energy consumption and travel time per round trip are obtained, based on which the recurring costs are computed by taking traffic demand into account. The horizontal and vertical alignments are jointly optimized with the train speed profile based on the computed recurring and initial expenses, which include rolling stock, earthwork, bridge, tunnel, right-of-way, and length-dependent construction costs. A case study and sensitivity analyses are presented to discuss the impacts of traffic demand on the optimized railway alignment. The effectiveness of the speed profile optimization method is demonstrated by comparing its simulated results with those without speed control.

High Voltage DC Auto-Transformer Traction Power Supply for Braking Energy Utilization, Rail Potential, and Stray Current Mitigation

For urban rail transit, high-voltage ac power is generally transmitted from the main substation to the traction substation (TS), which employs isolated diode–rectifiers to feed the dc traction power supply system. The train current feeds back to the negative cubicle of TS through the running rail, which is not totally isolated from the Earth. However, the traditional traction power supply (TTPS) shows limitations on braking energy-wasting, high rail potential, stray current, and so on. Thus, a high-voltage dc autotransformer (DCAT) traction power supply (HDATPS) is proposed in this article. Both configurations and principles of three typical HDATPSs are analyzed, which mainly consists of the dc main substation, the dc TS, and the DCAT substation. Then, through modeling of HDATPS and TTPS, the comparisons on braking energy utilization, rail potential, and stray current mitigation are discussed in detail. Finally, the simulation model and experimental platform of HDATPS are built, respectively, and the theoretical analysis is verified with the simulation and experimental results.

Modeling of Regenerative Braking Energy for Electric Multiple Units Passing Long Downhill Section

The process of electric multiple units (EMUs) passing long downhill sections is inevitable in the construction of mountain railways. Moreover, huge regenerative braking energy (RBE) will be sent back to the traction network, threatening voltage safety. Due to the lack of accurate vehicle-grid integrated models considering slope parameters in studying the RBE, this article proposes a modeling scheme, taking China railway high-speed 3 (CRH3) EMUs as an example. First, based on the extended dual pulsewidth modulation (PWM) mathematical model, the quantitative formula for calculating the motor braking power of the CRH3 EMUs is established. Moreover, the slope parameters are introduced into the vehicle-grid model via force analysis and regenerative braking power calculation. Then, by substituting the calculated results into the extended dual PWM mathematical model, the target instruction parameters are solved. Next, the accurate electrical characteristics, including catenary voltage, electromagnetic torque, and converter voltage, are simulated to evaluate the voltage safety. Finally, by comparing the simulation and semi-physical experiment results with the experimental data from the Chengdu to Chongqing railway line, the feasibility, validity, and accuracy of the model are verified.

Real-Time Control Strategy of Tractive Load Peak Clipping and Valley Filling Based on Model Predictive Control

Access to energy storage devices (ESDs) is an effective way to solve the peak traction load shock and Regenerative Braking Energy (RBE) recycling. However, in the real-time operation of the system, there are problems of prediction errors affecting the control results and the problem of energy storage “dead time.” This article analyzes the mechanism of the energy storage “dead-time” problem and aims to solve this problem without increasing the energy storage capacity. Therefore, this article combines the ideas of rolling optimization and predictive control in the model predictive control (MPC) method and proposes an MPC method based on the adaptive correction (AC-MPC) of the State of Charge (SOC) of ESD. The predictive control can ensure the accuracy of power correction; the rolling optimization can reduce the global impact of each correction and reduce the complexity of the calculation. In addition, the rolling prediction in the rolling optimization link reduces the prediction error by reducing the prediction time scale, thus reducing the impact of the prediction error on the control results. The experimental data show that the proposed control strategy can effectively solve the two problems mentioned above, ensure the effect of peak reduction and RBE recovery, and improve the economy of system operation.

Study on Energy-Saving Optimization of Urban Rail Transit Train Timetable under Regenerative Braking

Energy-saving driving and regenerative braking energy utilization are two main ways to realize energy-saving optimization of urban rail transit train timetables. On the basis of the more mature energy-saving driving achievements of the predecessors, the absorption utilization rate of regenerative braking energy is improved by adjusting the dwell time of trains in the station so that while a train is braking, other trains in the same electric section are just under traction. In this paper, the overlap time between the traction and braking processes of different trains is used as a measure of the proportion of regenerative braking energy that is absorbed. In order to maximize this overlap time, an energy-saving optimization model of urban rail transit train timetable based on regenerative braking technology was established. To facilitate the solution, the nonlinear constraints are converted to linear at the time of model construction in this paper. In the solution, the spatio-temporal local rolling algorithm and the commercial optimization software ILOG CPLEX are used for the solution. The solution results show that the method in this paper can effectively improve the absorption and utilization of regenerative braking energy.

Design of a Hybrid Electric Power-Split Transmission for Braking Energy Recovery in a Drilling Rig

Despite the promising potential of the hybrid electric power-split layout, its broader market penetration is prevented by the large number of feasible solutions and the constructive complexity, which overcomplicate the design process. Moreover, due to the lack of relevant literature references, the power-split transmissions design is even more difficult if concerning applications outside the automotive and agricultural sectors. In this paper, a general parametric model already available in the literature to design a single-mode power-split transmission with up to two planetary gear sets and six ordinary gear sets was applied to hybridize an oil drilling rig to recover energy braking during the gravity-driven lowering phases. This is the first power-split electric hybridization of a drilling rig. Two solutions differing in engine power size are presented. Thanks to the modularity of the model, the procedure enabled the optimization of the ICE, the electric machines, and the gear sets through decoupled design phases.

Optimal dispatching of high-speed railway power system based on hybrid energy storage system

High-speed railway power system consists of traction power system and station power system. High-speed railway locomotives generate electrical energy that is fed back to the grid during regenerative braking, and the grid company adopts the policy of ignoring the reverse transmission, which wastes energy on the railway system. In this paper, based on the interconnection of 10kV station power system and 27.5 kV traction power system, a hybrid energy storage system (HESS) composed of supercapacitors (SCs) and batteries is added to recover the regenerative braking energy, and roof photovoltaic (PV) is installed in railway station to reduce the power consumption of the system, and an energy management strategy with grid peak shaving characteristics is proposed. Then, the optimal dispatching model of high-speed railway power system is established, and the daily operation cost of the system is reduced by using the mixed integer linear programming method. Finally, according to the actual data of a domestic railway station, the proposed optimization method is verified. The results show that the strategy not only reduces the total daily operation cost, but also effectively reduces the peak power purchase of the peak load. The scheme proposed in this paper saves 11.86% of the daily operation cost.

Sizing and Performance Analysis of Hydrogen- and Battery-Based Powertrains, Integrated into a Passenger Train for a Regional Track, Located in Calabria (Italy)

In order to decarbonize the rail industry, the development of innovative locomotives with the ability to use multiple energy sources, constituting hybrid powertrains, plays a central role in transitioning from conventional diesel trains. In this paper, four configurations based on suitable combinations of fuel cells and/or batteries are designed to replace or supplement a diesel/overhead line powertrain on a real passenger train (the Hitachi Blues) tested on an existing regional track, the Catanzaro Lido–Reggio Calabria line (Italy), managed by Trenitalia SpA. (Italy). The configurations (namely battery–electrified line, full-battery, fuel cell–battery–electrified line, and fuel cell–battery) are first sized with the intention of completing a round trip, then integrated on board with diesel engine replacement in mind, and finally occupy a portion of the passenger area within two locomotives. The achieved performance is thoroughly examined in terms of fuel cell efficiency (greater than 47%), hydrogen consumption (less than 72 kg), braking energy recovery (approximately 300 kWh), and battery interval SOC.

Regenerative Braking Control Strategy with Real-Time Wavelet Transform for Composite Energy Buses

In order to meet the safety requirements of automobile braking, to improve the braking energy recovery rate of pure electric buses and increase their driving range, the maximum regenerative braking force that the motor can provide is used to determine the front and rear wheel friction braking force distribution curve. A parallel regenerative braking control strategy, A, is proposed to make full use of the motor performance. Aiming at the problems of low power density and short cycle life with a single power battery, a composite energy system composed of power batteries and supercapacitors is designed, and an alternative energy control strategy, D, using real-time wavelet transform control is proposed. The required power is decomposed into high-frequency components and low-frequency components by using the wavelet transform control, in which the high-frequency power is borne by the supercapacitor to avoid impact on the power battery. The simulation model was created using MATLAB/Simulink software, and the simulation was carried out under combined cycle conditions to verify the effectiveness of the control strategy. The simulation results showed that compared with the original vehicle control strategy, adopting the A regenerative braking control strategy can reduce the battery SOC drop by 5.15%, increase the relative increase by 47.9%, and improve the braking energy recovery rate. Compared with the traditional logic threshold regenerative braking control strategy, AC, the AD control strategy can effectively reduce the impact of the peak current and high-frequency demands of the power battery on the battery. The maximum output current of the battery was reduced by 39.5%. The decrease in battery SOC decreased by 0.69%, and the relative increase increased by 12.43%. The driving range and braking performance of the vehicle have thus been effectively improved.

Electric Vehicle Location Routing Problem With Vehicle Motion Dynamics-Based Energy Consumption and Recovery

In this article we deal with the main critical issues of using electric vehicles in urban transport given the battery related limitations on driving range, and the network layout related limitations on the number of recharging stations. In this context, we seek the optimal routing plans together with the optimal locations of recharging stations for electric vehicle fleets through the Electric Vehicle Location Routing Problem with Intermediate Nodes (ELRP-IN) we propose. The ELRP-IN we formulate as a mathematical program considers the actual characteristics of battery discharging and recovering the braking energy. Energy consumption and recovery are determined through vehicle motion dynamics in conjunction with the 3-dimensional feature of the road geometry, passengers’/customers’ demands on getting on and off, and the pre-defined speed profiles, where the graph corresponding to the road network is extended with the explicit consideration of intersections. By alternating the objectives adopted in the ELRP-IN formulation, we discuss through a number of numerical experiments involving real case instances the effects of both the objective functions and the parameters, including the consumption and the gain of energy, cost, traveled distance, and travel time, on the routing plans. Highlighting the finding that energy is not recovered in all the sections with descending grade, we reveal the direct effect of the elevation on the energy consumption, and hence on the location of a recharging station, where we discuss as well the limitation on energy recovery.

Hybridization of battery and ultracapacitor for electric vehicle application with dynamic energy management and non-linear state feedback controller

• Proposed a dynamic energy management system for hybrid sources in an electric vehicle. • Buck-boost H-bridge converters are introduced for bidirectional power flow control. • System non-linearities are addressed using a nonlinear state feedback controller. • The proposed system accurately delivers instantaneous vehicle speed and torque. This paper describes a methodology to control a multi-source battery-capacitor hybrid EV incorporating a dynamic power splitting strategy. Considering the requirement for precise speed control characteristics of the EV and the non-linear behavior of traction motor with system disturbances, a non-linear state feedback controller (NLSFC) with a disturbance observer is suggested as the speed control technique for the EV traction motor. To interface a parallel configured multi-source system, a non-inverted buck-boost H-bridge is proposed as the source side converter for effective recovery of the braking energy. Detailed control design for traction motor and converter is also presented for efficient control of EV. Besides, an adaptive energy management strategy considering power profile and dynamic source characteristics is incorporated into the overall control system. The simulation results from various case studies indicate that the proposed system can follow the required vehicle speed and torque despite the sudden change in EV load torque. Furthermore, the comparative analysis between NLSFC and PI controller shows improvement with steady-state error reduction from 0.43 to 0.0014 and peak overshoot drop from 12.07% to 3.51% during acceleration of the system when proposed NLSFC is adopted. The proposed solutions will be implemented in a prototype EV system in the future.