Bus mass estimation algorithm based on kinetic energy theorem

Bus mass is an important factor that affects fuel consumption and one of the key input parameters associated with automatic shift and hybrid electric vehicle （HEV） energy management strategy. A city bus mass estimation method based on kinetic energy theorem was proposed in this paper. The real-time data including vehicle speed and engine torque were collected by a remote data acquisition system. The samples in the process of being accelerated were selected to conduct vehicle mass estimation at the same bus stop with the same gear. The average estimation error is 2. 92% after the verification by actual data. Compared with the method based on recursive least squares, the algorithm based on kinetic energy theorem requires less sample length and the estimation error is smaller. Therefore, the method is more suitable for the bus mass estimation. The influences of gear, rolling resistance coefficient, wind resistance coefficient and road slope on mass estimation accuracy were analyzed.

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

DEVELOPMENT OF THE ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC URBAN BUSES

A novel parallel hybrid electrical urban bus （PHEUB） configuration consisting of an extra one-way clutch and an automatic mechanical transmission （AMT） is taken as the study subject. An energy management strategy combining a logic threshold approach and an instantaneous optimization algorithm is proposed for the investigated PHEUB. The objective of the energy management strategy is to achieve acceptable vehicle performance and drivability requirements while simultaneously maximizing the engine fuel consumption and maintaining the battery state of charge in its operation range at all times. Under the environment of Matlab/Simulink, a computer simulation model for the PHEUB is constructed by using the model building method combining theoretical analysis and bench test data. Simulation and experiment results for China Typical Bus Driving Schedule at Urban District （CTBDS_UD） are obtained, and the results indicate that the proposed control strategy not only controls the hybrid system efficiently but also improves the fuel economy significantly.

A Multi-slack Bus Model for Bi-directional Energy Flow Analysis of Integrated Power-gas Systems

The bi-directional energy conversion components such as gas-fired generators(GfG)and power-to-gas(P2G)have enhanced the interactions between power and gas systems.This paper focuses on the steady-state energy flow analysis of an integrated power-gas system(IPGS)with bi-directional energy conversion components.Considering the shortcomings of adjusting active power balance only by single GfG unit and the capacity limitation of slack bus,a multi-slack bus(MSB)model is proposed for integrated power-gas systems,by combining the advantages of bi-directional energy conversion components in adjusting active power.The components are modeled as participating units through iterative participation factors solved by the power sensitivity method,which embeds the effect of system conditions.On this basis,the impact of the mixed problem of multi-type gas supply sources(such as hydrogen and methane generated by P2G)on integrated system is considered,and the gas characteristics-specific gravity(SG)and gross calorific value(GCV)are modeled as state variables to obtain a more accurate operational results.Finally,a bi-directional energy flow solver with iterative SG,GCV and participation factors is developed to assess the steady-state equilibrium point of IPGS based on Newton-Raphson method.The applicability of proposed methodology is demonstrated by analyzing an integrated IEEE 14-bus power system and a Belgian 20-node gas system.

Variable Parameter Self-Adaptive Control Strategy Based on Driving Condition Identification for Plug-In Hybrid Electric Bus

A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.

Comparison of In-Use Operating Costs of Hybrid-Electric and Conventional School Buses

Hybrid-electric school buses became available in the US through a national consortium designed to bring hybrid-electric school buses to market by creating enough demand among school districts to encourage manufacturers to invest in development of the technology. A number of school districts in the US joined the HESB project to purchase plug-in hybrid-electric school buses. Sixteen hybrid-electric school buses were purchased and piloted in 11 states. Two of the hybrid-electric school buses were purchased by the Nevada and Sigourney school districts in the state of Iowa, US. In-use fuel economy and electricity operating costs were monitored for the two Iowa hybrid school buses and two control buses (one in each district). Fuel consumption and other operational metrics were calculated and compared for each school district. The hybrid buses were deployed in January 2008 and data were recorded through May 2010. Valuation of the data indicated that the Nevada HESB had 29.6% better fuel economy than the control bus and the Sigourney HESB had 39.2% better fuel economy than the control bus. Electrical costs per mile were also calculated for the two hybrid-electric school buses. Total operating costs per mile were calculated based on fuel use per mile for all buses and electrical costs for the hybrid-electric school buses. The cost to operate the hybrid bus in Nevada was 37 cents/mile while the control bus cost 42 cents/mile, making the hybrid bus 13% less expensive to operate. The hybrid bus in Sigourney was 27 cents/mile while the control bus was 34 cents/mile, making the hybrid bus 21% less expensive to operate. All values are in US dollars.

Research on Intelligent Power Management System for Student Dormitory based on CAN Bus

This paper analyzes the actual situation of the electricity management about student apartments, and design intelligent energy student housing management system based on CAN bus. The system uses the field level, the underlying management level and upper management level three management system. Field level with a dedicated energy metering chip AD7755 and STM32F103 microcontroller with A/D conversion function as the core, to achieve real-time power measurement; via CAN bus timing or random read live energy data for monitoring electricity consumption of the apartment, investigate abnormal electricity, thus effectively limiting the students to use electrical power to achieve the modernization and automation of power management solutions student apartments.

Half‑Power Prediction and Its Application on the Energy Management Strategy for Fuel Cell City Bus

The fuel cell hybrid powertrain is a potential power supply system for fuel cell vehicles.The underlying problem is that the fuel cell vehicles encounter exhaustive hydrogen consumption.To effectively manage hydrogen consumption,the aim is to propose fuel cell city bus power and control system.The underlying idea is to determine the target power of fuel cell through simulation study on fuel cell and battery energy management strategy and road test verifications.A half-power prediction energy management strategy is implemented to predict the target power of the fuel cell in the current time step based on the demand power of the vehicle and the state of charge(SOC)of the battery in the previous time steps.This offers better understanding of the correlation between fuel cell power and vehicle drive cycle for enabling effective power supply management.The research results show that the half-power prediction energy management strategy effectively reduces the hydrogen consumption of the vehicle by 7.1%and the number of battery cycle by 6.0%,compared to the stepped manage-ment strategy of battery SOC.When applied to a 12-m fuel cell city bus—F12,specially designed and manufactured for the Winter Olympic Games in 2022—the fuel economy of 3.7 kg/100 km is achieved in urban road conditions.This study lays a foundation for providing the powertrain configuration and energy management strategy of fuel cell city bus.

A network-based virtual slack bus model for energy conversion units in dynamic energy flow analysis

Integrated energy system(IES) is a viable route to “carbon peak and carbon neutral”. As the basis and cornerstone of economic operation and security of IES, energy flow calculation(EFC) has been widely studied. Traditional EFC focuses on the single or distributed slack bus models, which results in the lack of unlimited power to maintain system operation, especially for electric power grid working in islanded or coupled mode. To deal with this problem, this paper proposes a network-based virtual-slack bus(VSB) model in EFC. Firstly, considering the anticipated growth of energy conversion units(ECUs) with power adjustment capacity, the generators and ECUs are together modeled as a virtual slack bus model to reduce the concentrated power burden of IES. Based on this model, a power sensitivity method is designed to achieve the power sharing among the ECUs, where the power can be allocated adaptively based on the network conditions. Moreover, the method is helpful to maintain the voltage and pressure profile of IES. With these changes, a dynamic energy flow analysis including virtual slack bus types is extended for IES.It can realize the assessment of the system state. Finally, simulation studies illustrate the beneficial roles of the VSB model.

Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.

碳中和城市建筑能源系统(4):储能篇

本文是碳中和城市建筑能源系统系列文章的第四篇。在碳中和语境下,无论是增加可再生能源应用的渗透率,还是平抑负荷、提高电网的灵活性,都离不开储能。本文介绍了当今储能技术的主要类型,即电力、电化学、机械、化学和热储能。重点介绍了与建筑和区域能源系统有关的储能技术。提出了用于第5代区域供热供冷系统(能源总线系统)的季节性热储能的概念性方案,并对在能源总线系统规划中如何考量储能应用提出了建议。指出在全球气候变化背景下结合热泵的应用,季节性热储能技术应是今后关注的重点。

碳中和城市建筑能源系统(2):网络篇

本文是碳中和城市建筑能源系统系列文章的第二篇,分别概要介绍了城市能源系统中的电网、热网和燃气网在碳中和背景下的新概念、新技术及新方法。强调未来的能源网以电网为主,三网融通,构成城区的能源互联网。综述了智能电网的灵活性、热泵在智能电网中的重要作用、城区能源总线中的负荷多样性和保持网络水温的技术、基于CO_(2)的区域能源网络,以及城区层面氢燃料的制备、输送、储存等技术问题。

Integrated Energy System Planning at Modular Regional-user Level Based on a Two-layer Bus Structure

An integrated energy system(IES)planning method with modular simulation and optimization models is proposed in this paper.A two-layer bus structure is adopted in the simulation model,where the external bus structure is used for power balance while the internal bus structure simulates the fast dynamics of electricity and slow dynamics of heat network in detail.In addition,an improved self-adaptive genetic algorithm(GA)is adopted in the optimization model to solve the multi-dimension and multi-time-scales optimization problem for the regional-user level IEPS.The proposed method can improve the extension flexibility of the system optimal planning model with expected accuracy.A case study is used to verify the effectiveness of the proposed planning method.

Implementable Strategy Research of Brake Energy Recovery Based on Dynamic Programming Algorithm for a Parallel Hydraulic Hybrid Bus

The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.

Configuration design,energy management and experimental validation of a novel series-parallel hybrid electric transit bus

This paper aims to present the configuration design approach and the energy management strategy （EMS） of a series-parallel hybrid electric transit bus （SPHEB） jointly developed by Shanghai Automotive Industry Co. Ltd. （SAIC） and Shanghai Jiao Tong University （SJTU）, China. A major feature of this SPHEB is that a novel manual transmission is designed to switch the powertrain configuration between series and parallel types. To reduce the fuel consumption as well as sustain the battery state of charge, an EMS including seven energy flow modes is designed and applied to this SPHEB. Governed by this EMS, the engine is maintained to operate in high efficiency regions. The experimental test carded on the transit bus city driving cycle is described and analyzed. The experimental results demonstrate the technical feasibility and fuel economy of this approach.

Trip energy consumption estimation for electric buses

This study aims to develop a trip energy consumption(TEC)estimation model for the electric bus(EB)fleet planning,operation,and life-cycle assessment.Leveraging the vast variations of temperature in Jilin Province,China,real-world data of 31 EBs operating in 14 months were collected with temperatures fluctuating from
27.0 to 35.0℃.TEC of an EB was divided into two parts,which are the energy required by the traction and battery thermal management system,and the energy required by the air conditioner(AC)system operation,respectively.The former was regressed by a logarithmic linear model with ambient temperature,curb weight,travel distance,and trip travel time as contributing factors.The optimum working temperature and regression parameters were obtained by combining Fibonacci and Weighted Least Square.The latter was estimated by the operation time of the AC system in cooling mode or heating mode.Model evaluation and sensitivity analysis were conducted.The results show that:(i)the mean absolute percentage error(MAPE)of the proposed model is 12.108%;(ii)the estimation accuracy of the model has a probability of 99.7814% meeting the requirements of EB fleet scheduling;(iii)the MAPE has a 1.746% reduction if considering passengers’boarding and alighting.

An Advanced FMRL Controller for FACTS Devices to Enhance Dynamic Performance of Power Systems

The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system （FACTS） in this paper is an advanced super-conducting magnetic energy storage （ASMES）. Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller （FMRLC） is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters （i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met）. Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system （i.e., single machine-infinite bus （SMIB） system）, under various fault conditions and disturbances.

"CHALCO-made" New Energy Bus Makes Debut

On March 3,The first'CHALCO-made'bus with an all-aluminum body has been successfully assembled at CHALCO Southwest Aluminum('SWA')Electromechanical Equipment Company,marking the completion of the'CHALCO-made'pilot Shudu bus project.The'CHALCO-made'new energy bus is 400 kg lighter with a residual body value of more than RMB 8,000.

Study of n-γ discrimination in low energy range(above 40 keVee) by charge comparison method with a BC501A liquid scintillation detector

A VME-based experiment system for n-y discrimination using the charge comparison method was established.A data acquisition program for controlling the programmable modules and processing data online via VME64X bus was developed through the use of Lab VIEW.The two-dimensional（2D） scatter plots of the charge in the slow component vs.the total charge from ^（241）Am-Be and 252Cf neutron sources are presented.The 2D scatter plots of the energy vs.the ratio of the charge in the slow component to the total charge of the pulses are also presented.The quality of n-γ discrimination was checked by the figure-of-merit,and the results showed good performance of n-γ discrimination at the low energy range.Neutrons and γ-rays were separated above 50 keVee（electron-equivalent energy）.The quality of n-γ discrimination has been improved compared with others＇ results at five energies（150,250,350,450,550 keVee）.