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.

Control system design of hybrid fuel cell city bus

This paper introduced the design of the hybrid powertrain of the Fuel Cell City Bus demonstrated in 2008 Beijing Olympic Games. The configuration of the hybrid fuel cell powertrain was introduced. The safety of hydrogen storage and delivery system, the hydrogen leakage alarm system were developed. The real-time distributed control and diagnosis system based on the Time Trigger Controller Area Network （TTCAN） with 10 ms basic control period was developed. The concept and implementation of processor （or controller） monitor and process （or task） monitor technique based on the TYCAN were applied in this paper. The fault tolerant control algorithm of the fuel cell engine and the battery man- agement system were considered. The demonstration experience verified that the fault tolerant control was very important for the fuel cell city bus.

Input Split Hydraulic Hybrid Bus and Control Strategy

Simple and efficient energy management strategy is the key to ensure hybrid vehicle performance. Based on hybrid dynamical system theory and the concept of finite state mechanism,power split hybrid connected structure hydraulic hybrid system was proposed and described. In order to meet the demand for driving,the layered advanced control strategy was proposed in this paper,which referred to vehicle driving experience. Using Matlab /Simulink /Stateflow hybrid modeling method, the economy performance and the acceleration performance of the vehicle under the typical city driving cycles were carried on the simulation analysis. The results show that the proposed topology and control strategy can obviously improve engine output characteristic,effectively enhance the vehicle's instantaneous power performance and economy,and also has a better adaptability in different traffic environments.

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.

Study on the Effect of Multi-Type Current Transformers Hybrid Operation on Differential Protection of the Bus Based on Dynamic Simulation

This paper analyzes characteristics of multi type current transformers hybrid operation for each branch of the bus and their effects on differential protection of the bus. By theoretically analyzing transmission characteristics of multi type current transformers and their influence factors, we study the dynamic model testing method of multi type current transformers for the bus, and design 3 kinds of testing schemes by making the equivalent model based on the field of P-level current transformer, TPY-level current transformer and electronic current transformer, and build the hybrid operation testing platform of multi type current transformers. Finally, we compare and analyze the transmission characteristics difference of multi type current transformers on the same branch and the characteristics difference of hybrid operation in two successive external faults, analyze the cause behind the differences, and put forward the corresponding improvement measures.

Support Vector Regression for Bus Travel Time Prediction Using Wavelet Transform

In order to accurately predict bus travel time, a hybrid model based on combining wavelet transform technique with support vector regression(WT-SVR) model is employed. In this model, wavelet decomposition is used to extract important information of data at different levels and enhances the forecasting ability of the model. After wavelet transform different components are forecasted by their corresponding SVR predictors. The final prediction result is obtained by the summation of the predicted results for each component. The proposed hybrid model is examined by the data of bus route No.550 in Nanjing, China. The performance of WT-SVR model is evaluated by mean absolute error(MAE), mean absolute percent error(MAPE) and relative mean square error(RMSE), and also compared to regular SVR and ANN models. The results show that the prediction method based on wavelet transform and SVR has better tracking ability and dynamic behavior than regular SVR and ANN models. The forecasting performance is remarkably improved to obtain within 6% MAPE for testing section Ⅰ and 8% MAPE for testing section Ⅱ, which proves that the suggested approach is feasible and applicable in bus travel time prediction.

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.

A high-fidelity memory scheme for quantum data buses

A novel quantum memory scheme is proposed for quantum data buses in scalable quantum computers by using adjustable interaction. Our investigation focuses on a hybrid quantum system including coupled flux qubits and a nitrogen–vacancy center ensemble. In our scheme, the transmission and storage（retrieval） of quantum state are performed in two separated steps, which can be controlled by adjusting the coupling strength between the computing unit and the quantum memory. The scheme can be used not only to reduce the time of quantum state transmission, but also to increase the robustness of the system with respect to detuning caused by magnetic noises. In comparison with the previous memory scheme, about 80% of the transmission time is saved. Moreover, it is exemplified that in our scheme the fidelity could achieve 0.99 even when there exists detuning, while the one in the previous scheme is 0.75.

Transient Characteristics and Accommodative Current Limiting Strategy for Bidirectional Interlinking Converters in Hybrid AC/DC Microgrids

Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC sub-grids.However,the variety of control modes and flexible bidirectional power flow complicate the influence of AC faults on BIC itself and on DC sub-grid,which potentially threaten both converter safety and system reliability.This study first investigates AC fault influence on the BIC and DC bus voltage under different BIC control modes and different pre-fault operation states,by developing a mathematical model and equivalent sequence network.Second,based on the analysis results,a general accommodative current limiting strategy is proposed for BIC without limitations to specific mode or operation condition.Current amplitude is predicted and constrained according to the critical requirements to protect the BIC and relieving the AC fault influence on the DC bus voltage.Compared with conventional methods,potential current limit failure and distortions under asymmetric faults can also be avoided.Finally,experiments verify feasibility of the proposed method.

混合动力客车道路滑行试验研究

在交通部某试验场长直线道路上,对一辆混合动力客车进行制动能量回收系统关闭和开启、变速器空挡和挂挡以及65%载荷和满载条件下滑行比对试验,以研究制动能量回收系统、变速器挡位以及载荷对车辆滑行阻力造成的影响.结果表明,制动能量回收过程中产生的再生制动力与车速近似成二次函数关系,对车辆滑行阻力影响最大;挂档条件下客车滑行阻力大小与车速成正比,滑行阻力值比空挡条件下约高2 200 N;满载滑行阻力值比65%载荷高约5%～15%,对滑行阻力值影响相对较小.进行道路滑行试验时,混合动力客车的制动能量回收系统关闭.变速器置空挡.

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.

Development and experimental validation of a novel hybrid powertrain with dual planetary gear sets for transit bus applications

Given that energy conservation and environmental protection are two important goals for the automotive industry, the application of a hybrid electric powertrain can improve vehicle energy efficiency while decreasing fuel consumption and engine emissions. Planetary gear-based power-split hybrid powertrains have become widely used in passenger vehicles, but remain rarely employed on transit buses. This study proposes a novel hybrid powertrain based on two planetary gear sets(CHS) and presents its operating principles along with development of a control strategy for the powertrain. The CHS hybrid powertrain operates in electric mode when the driving power demand is low, and changes to a hybrid electric mode according to the power-split principle of the planetary gear set. To validate the feasibility of the designed CHS hybrid powertrain, a prototype transit bus equipped with the designed hybrid powertrain system was built, and the operating characteristics of the system were analyzed through a performance test conducted on a chassis dynamometer. Compared with a conventional powertrain, the CHS hybrid powertrain can reduce fuel consumption by 39%. Thus, the CHS hybrid powertrain is a good solution for heavy-duty applications such as hybrid transit buses because of its simple structure and excellent fuel efficiency.

Multi-objective parameter optimization for a single-shaft series-parallel plug-in hybrid electric bus using genetic algorithm

Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus （PHEB） has become one of the most popu- lar powertrains due to its alterable operating modes, excellent fuel economy and strong adaptability for driving cycles. Never- theless, for configuring the PHEB with single-shaft series-parallel powertrain in the development stage, it still faces greater challenge than other configurations when choosing and matching the main component parameters. Motivated by this issue, a comprehensive multi-objectives optimization strategy based on Genetic Algorithm （GA） is developed for the PHEB with the typical powertrain. First, considering repeatability and regularity of bus route, the methods of off-line data processing and mathematical statistics are adopted, to obtain a representative driving cycle, which could well reflect the general characteristic of the real-world bus route. Then, the economical optimization objective is defined, which is consist of manufacturing costs of the key components and energy consumption, and combined with the dynamical optimization objective, a multi-objective op- timization function is put forward. Meanwhile, GA algorithm is used to optimize the parameters, for the optimal components combination of the novel series-parallel powertrain. Finally, a comparison with the prototype is carried out to verify the per- formance of the optimized powertrain along driving cycles. Simulation results indicate that the parameters of powertrain com- ponents obtained by the proposed comprehensive multi-objectives optimization strategy might get better fuel economy, meanwhile ensure the dynamic performance of PHEB. In contrast to the original, the costs declined by 18%. Hence, the strat- egy would provide a theoretical guidance on parameter selection for PHEB manufacturers.

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.

Timetable optimization for single bus line based on hybrid vehicle size model

This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.

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.