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.

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.

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.

MPC‑Based Coordinated Control of Gear Shifting Process for a Power‑split Hybrid Electric Bus with a Clutchless AMT

Two-speed clutchless automated manual transmission(AMT)has been widely implemented in electric vehicles for its simple structure and low cost.In contrast,due to the complex response characteristics of powertrain,utilizing clutchless AMT in a hybrid power system comes with complex coordination control problems.In order to address these issues,a power-split hybrid electric bus with two-speed clutchless AMT is studied in this paper,and a coordinated control method based on model predictive control(MPC)is used in gear shifting control strategy(GSCS)to improve gear shifting quality and reduce system jerk.First,the dynamic model of power sources and other main powertrain components including a single planetary gear set and AMT are established on the basis of data-driven and mechanism modeling methods.Second,the GSCS is put forward using the segmented control idea,and the shifting process is divided into five phases,including(I)unloading of drive motor,(II)shifting to neutral gear,(III)active speed synchronization by drive motor,(IV)engaging to new gear,and(V)resuming the drive motor’s power,among which the phases I and V have evident impact on the system jerk.Then,the MPC-based control method is adopted for these phases,and the fast compensation of driving torque is realized by combining the prediction model and quadratic programming method.The simulation results show that the proposed GSCS can effectively reduce shift jerk and improve driving comfort.This research proposes a coordinated control strategy of two-speed clutchless AMT,which can effectively improve the smoothness of gear shifting and provides a reference for the application of two speed clutchless AMT in power-split hybrid powertrains.

A Novel Braking Control Strategy for Hybrid Electric Buses Based on Vehicle Mass and Road Slope Estimation

Proper braking force distribution strategies can improve both stability and economy performance of hybrid electric vehicles,which is prominently proved by many studies.To achieve better dynamic stable performance and higher energy recovery efficiency,an effective braking control strategy for hybrid electric buses(HEB)based on vehicle mass and road slope estimation is proposed in this paper.Firstly,the road slope and the vehicle mass are estimated by a hybrid algorithm of extended Kalman filter(EKF)and recursive least square(RLS).Secondly,the total braking torque of HEB is calculated by the sliding mode controller(SMC),which uses the information of brake intensity,whole vehicle mass,and road slope.Finally,comprehensively considering driver’s braking intention and regulations of the Economic Commission for Europe(ECE),the optimal proportional relationship between regenerative braking and pneumatic braking is obtained.Furthermore,related simulations and experiments are carried out on the hardware-in-the-loop test bench.Results show that the proposed strategy can effectively improve the braking performance and increase the recovered energy through precise control of the braking torque.

DESIGN AND EXPERIMENT OF ELECTRIC BUS

Performance and reliability experiments on BJD-6100EV electric buses, jointlydeveloped by Beijing Institute of Technology and Beijing Public Transport Company, are introduced.Output power model of battery pack is established and maximum output power is analyzed. A permanentmagnetic direct current (PMDC) motor with enhanced windings is developed for the bus. Torque-speedcharacteristics of the motor are modeled and performance of electric bus is analyzed. Computationalmethod of the range of electric bus is proposed and discussed. Experiments show that electric buscan realize design requirements. Computational methods are verified with the help of field test. Itis expected that design and computation method will provide helpful reference to development ofelectric vehicles.

Analysis of Control Characteristic for the Drive System of Electric Transit Bus

The drive control system of the permanent magnetic direct current motor with the enhanced magnetism windings used in the electric transit bus is developed. The mathematics model of the drive control system for this motor is established. The new mode that the added exiting magnetism field could be weakened and the speed of the motor could be controlled automatically is proposed and realized. The method of root locus design is applied to analyze the acceleration control characteristic. The results of simulation show that the new drive motor control system has extraordinary response characteristic and adjustable performance. Experiments of vehicle running show that the drive control system's antijamming ability is strong and the adjustable performance is fast and smooth, it can meet the demand of power characteristic very well.

Operational program for proper capacity of electric bus charging station in Expo 2010

In the paper,an operational program of electric bus charging station is proposed,which is special for "The Construction Project for Expo 2010 Temporary Electric Bus Charging Station".Based on the quick-change mode,a vehicle operating schedule model has been established to meet the capacity of transport.Then,according to the quantity of passengers and utilization of batteries,a calculative method of parameters,such as the number of spare batteries and bus departure rules,has been provided.Furthermore,optimal simulation software designed for operating process of the charging station has been identified incorporating actual running data from electric buses and monitoring system of the charging station,and the rationality of the design is verified in the preliminary commissioning and the official operation.

Parameter optimization of electric bus transmission system based on dynamical evolutionary algorithm

The transmission ratio is the key parameters influence power performance and economic performance of electric vehicle （EV）. As a class of heuristic algorithms, Dynamical Evolutionary Algorithm （DEA） is suitable to solve multi-objective optimization problems. This paper presents a new method to optimize the transmission ratio using DEA. The fuzzy constraints and objective function of transmission ratio are established for parameter optimization problem of electric bus transmission. DEA is used to solve the optimiza- tion problem. The transmission system is also designed based on the optimization result. Optimization and test results show that the dynamical evolutionary algorithm is an effective method to solve transmission parameter optimization problems.

Electric Buses in Urban Transport, The Situation and Development Trends

A study called ＂E-mobilita v MHD＂ （e-mobility in urban mass transit） has been conducted by the author＇s private consultancy to inform Czech public transport operators about the technologies and operational experience to date and stimulate the e-bus utilization as well as their involvement in e-bus research and development projects. The study covers trolley-buses, diesel hybrids and e-buses including fuel cell buses. These electric urban buses have been compared with combustion engine vehicles represented by diesel and CNG （compressed natural gas） buses, in terms of energy consumption and cost, greenhouse gas emissions, noise and life cycle cost. Relations between urban transport e-mobility and the ＂smart grid＂ concept have been presented as well. Comprehensive reports prepared on the European Union and the USA levels have been the basis for the study, completed by information from the field research, focused especially on the bus operational reliability and other parameters important for a transport operator and covering, interalia, 12 case studies. The results show electric buses as a promising urban transport mode with massive technology development overcoming their operational limitations. Synergies between electric buses and other urban systems, such as power supply, are notable as well.

Modeling the Prospects of Plug-In Electric Buses to Reduce GHG Emissions and Cost While Meeting Route Demands: A Case Study of the “Unitrans” Bus Fleet Serving the Davis, California Urbanized Area

As university campuses look to decrease their greenhouse gas emissions, plug-in electric buses may provide a low carbon alternative to conventionally fossil-powered buses. This study investigates the viability for Unitrans, the bus service for the greater Davis area and the university campus, to replace current compressed natural gas buses with plug-in electric versions. This study presents an inventory of market available electric buses, their associated costs, incentives, and infrastructure concerns, and compares projected energy use, net present cost, and greenhouse gas emissions with their CNG counterparts. ADVISOR vehicle simulation software is used to estimate the energy use of a typical electric bus (New Flyer Xcelsior XE40 300 kW) and compare to the current CNG model (Orion V) along an actual Unitrans route. The model estimates that the selected bus can travel 146 miles on a single charge, with a fuel economy of 1.75 kWh per mile, which meets the service requirements. Results for bus replacement schedules between 5 and 49 in the 12-year analysis period indicate that between 1600 and 22,000 MT of carbon can be avoided. The net present cost analysis indicates that the potential savings from the replacement of a single CNG bus with an electric bus (with available incentives) ranges from $146,000 - $211,000 per bus over its lifetime, depending on infrastructure costs.

Common Information Model： A Bus Service for Electric Calculations in AES Eletropaulo

This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power transmission and distribution area were evaluated, allowing the definition of state of the art on the theme, followed by determining its applications considering technologies already applied by the company. The specifications needed for the generation of a data integration model are adapted to radial overhead network at company concession area. The project developed an intermediary connectivity layer, based on the CIM （common information model）, which enables corporative systems to communicate in a standard way, through the use of integrating technologies. It, therefore, enabled modeling all main subjects of an electrical network in an open, extensible and non-proprietary way, in a model that contains classes and attributes of such subjects, as well as their relationships. Calculation and planning products adopted by the company were integrated to the technological layer implemented.

Design of the Control System about Central Signals in Electric Vehicle

Based on the development demand of electric vehicles, this paper studies the communication network in electric vehicles based on CAN bus after analyzing the LCD (liquid crystal display) in electric vehicles and the status quo of research and development trend about communication network. This system uses TMS320LF2407 DSP as the controller of the control system about central signals. It has also developed the LCD system based on CAN bus and the experiment platform which is applied pure electric vehicles.

The research of controller area network on hybrid electrical vehicle

It is of increasing importance to design and implement vehicle networks for transferring information between electrical control units on Hybrid Electrical Vehicle （HEV）. This paper presents a scheme of using Controller Area Network （CAN） technology to realize communication and datasharing between the electrical units on the HEV. The principle and communication protocol of Electrical Control Units （ECU） CAN node are introduced. By considering different sensitivity of the devices to the latency of data transportation, a new design procedure is proposed for the purpose of simplifying network codes and wiring harness, reducing assembly space and weight, improving assembly efficiency, and enhancing fault-diagnose in auto networks.

Research and Application of 40 kW Electric Servo System on Gravity-1 Launch Vehicle

This article introduces the 40 kW electric servo system used by Gravity-1 strap-on launch vehicle, which mainly includes the composition, function and related equipment of the system. Aiming at the measurement deviation caused by the closed loop of resolver, a compensation algorithm is designed;aiming at the monitoring of the output power of the thermal battery, an algorithm without sensory monitoring the bus current is designed. In the end, the effectiveness of the two algorithms was verified by testing.

Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

Coordinated Restoration Method for Electric Buses and Network Reconfigurations in Distribution Systems Under Extreme Events

Distribution systems are facing challenges in serving lifeline loads after extreme events.Network reconfiguration is a traditional and practical method for power supply restoration,which has strong but inflexible power transfer capabilities influenced by network topology.Multiple failures of utility power under extreme events will further limit the efficiency of network reconfiguration.Electric buses(EBs)can be utilized to achieve power supply considering their discharging capabilities as mobile storage devices.However,the mobility of EBs and the influences of transport systems must be carefully considered to enhance the resilience of distribution systems.Reconfiguration and EBs are complementary in terms of recovery capabilities and location flexibility,and more important loads can be recovered by the coordination between EBs and network reconfiguration.This paper proposes a coordinated restoration method for EBs and reconfigurations considering the influences of transport systems.The post-disaster restoration problem is formulated as a bi-level model,in which the network topology is optimized in the upperlevel aiming at maximizing restoration loads through the main grid and EBs,while the traffic paths of all EBs are optimized with the goal of maximizing the restoration loads by the EBs in the lower-level considering time consumption and energy consumption during movement.The PSO and a genetic algorithm are used to solve the proposed bi-level optimization problem.Simulation studies are performed to verify the superiority of the proposed method.

Study on control strategy of CAN bus network based on event triggered mode

In order to reduce the load rate of CAN bus and improve the real-time performance of control system, CAN bus control system of a pure electric vehicle is studied. Communication messages of each node are optimized and redefined by sorting the message into three types： control message, status message and alann message. Event triggered mode is added to the communication way of CAN bus, and the communication control strategy of the vehicle is made. It is proved that CAN bus load rate of control system is reduced after optimization, and the real-time performance of communication is improved effectively.

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.

A hybrid dynamic programming-rule based algorithm for real-time energy optimization of plug-in hybrid electric bus

The optimization of the control strategy of a plug-in hybrid electric bus(PHEB) for the repeatedly driven bus route is a key technique to improve the fuel economy. The widely used rule-based(RB) control strategy is lacking in the global optimization property, while the global optimization algorithms have an unacceptable computation complexity for real-time application. Therefore, a novel hybrid dynamic programming-rule based(DPRB) algorithm is brought forward to solve the global energy optimization problem in a real-time controller of PHEB. Firstly, a control grid is built up for a given typical city bus route, according to the station locations and discrete levels of battery state of charge(SOC). Moreover, the decision variables for the energy optimization at each point of the control grid might be deduced from an off-line dynamic programming(DP) with the historical running information of the driving cycle. Meanwhile, the genetic algorithm(GA) is adopted to replace the quantization process of DP permissible control set to reduce the computation burden. Secondly, with the optimized decision variables as control parameters according to the position and battery SOC of a PHEB, a RB control is used as an implementable controller for the energy management. Simulation results demonstrate that the proposed DPRB might distribute electric energy more reasonably throughout the bus route, compared with the optimized RB. The proposed hybrid algorithm might give a practicable solution, which is a tradeoff between the applicability of RB and the global optimization property of DP.