Pure Electric Mode Research Articles

The Coordinated Control Strategy of Engine Starting Process in Power Split Hybrid Electric Vehicle Based on Load Observation

During the process of moving, the power splitting hybrid vehicle is required to start the engine to transfer from pure electric mode to hybrid drive mode. According to the structural characteristics of the system, the engine starting process was divided into four stages, the engine starting process was established, and a multi-stage engine starting coordination control strategy was designed. In the engine reverse-drag process, the coordination control strategy was transformed into the optimal rotation rate tracker problem. In order to solve the load torque required in the tracking problem, a reduced-order observer was designed. Finally, the validity of the coordination control strategy was verified on the simulation platform of the electro-mechanical composite transmission system. The feasibility of the coordination control strategy was verified by hardware-in-the-loop simulation. The results show that the engine start coordination control strategy could achieve steady and fast engine start control. The maximal impact of the whole vehicle is reduced from 30 to 2.5 m/s3.

Electric-thermal collaborative control and multimode energy flow analysis of fuel cell hybrid electric vehicles in low-temperature regions

The energy flow distribution characteristics of electric vehicles operating in various propulsion modes and all climatic scenarios have not been thoroughly explored. To achieve effective electric-thermal collaborative energy management, intelligent control methods must be applied considering various climatic conditions to alleviate mileage anxiety. In this study, we developed a novel electric–thermal collaborative energy management strategy based on an improved deep neural network and energy quantification model to increase the global energy conversion efficiency. The complete energy consumption distribution characteristics are summarized under various strategies and propulsion modes based on an experiment data collected by the vehicle control unit that involves battery self-heating, cabin heating, acceleration consumption, and fuel consumption in the temperature range of −10°C-35 °C. Our findings indicate that, for a fuel cell hybrid bus in the cycle including the initial cabin heating process, the heating consumption in the pure electric mode was 9.9 kWh/cycle and 13 kWh/cycle when the ambient temperature is −2 °C and −10 °C, respectively, accounting for 33 % and 42 % of the total consumption, respectively. After using the waste heat from the fuel cell, the consumption of electric heating under the same conditions is only 3.7 kWh/cycle. In the high-temperature scenario, the cabin cooling consumption is 3.26 kWh/cycle, accounting for only 18 % of the total energy consumption. Finally, in low-temperature scenarios, the electric–thermal collaborative strategy reduced the cost by 14.7 % and 9.2 % in the pure electric and hybrid modes, respectively. Thus, our approach significantly improves energy utilization and conversion efficiency, especially at low temperatures.

Pure TE and TM modes in the metallic waveguide filled homogeneously with fully anisotropic and lossless medium

AbstractThis letter gives a sufficient condition for the existence of the pure transverse electric (TE) and transverse magnetic (TM) modes in the metallic waveguide filled with a homogeneous, fully anisotropic and lossless medium. The condition is a relation between the permittivity and permeability tensors of the fully anisotropic medium. The theory given in the letter is an extension of the classic electromagnetic waveguide theory. Furthermore, a mixed spectral element method is applied to simulate this type of anisotropic waveguide problem. At last, a numerical experiment shows that the sufficient condition supported in the letter does confirm the existence of the pure TE and TM modes in the anisotropic waveguide.

Engine Start‐Up Torque Coordinated Control for Multimode Hybrid Electric Vehicle Equipped With a Two‐Speed Dedicated Hybrid Transmission

A multimode hybrid electric vehicle (HEV) equipped with a dedicated hybrid transmission (DHT) can be generally divided into pure electric mode with engine shutdown and hybrid mode with engine operation. Engine start‐stop control is the key to achieving a transition between these two modes. To address the issues of engine start‐up torque coordination control and torque interference, first, the start‐up requirements of DHT‐HEV engines in different driving scenarios are summarized, a multistage dynamic model for DHT‐HEV engine start‐up is established, and the key issues of engine start‐up torque coordination control are analyzed. Second, an engine start‐up torque coordinated control strategy with torque interference and parameter uncertainty is proposed, a robust model predictive controller (RMPC) is designed to adjust clutch pressure, a finite time disturbance observer (FTDO) is designed to obtain torque interference during the engine start‐up process, and a sliding mode observer (SMO) is designed to obtain vehicle driving resistance torque. Finally, a simulation and hardware‐in‐the‐loop (HIL) test are conducted to verify the performance of the relevant observers, torque coordination control, and interference compensation control during the engine start‐up process.

Design and performance of a distributed electric drive system for a series hybrid electric combine harvester

In order to solve the problems of high energy consumption, high pollution and difficult adjustment of operational parameters caused by the coupling of operating components of conventional combine harvester, a novel series hybrid electric combine harvester (SHECH) is proposed. This paper is based on series hybrid power technology and distributed electric drive technology. The balance between SHECH energy consumption and endurance is coordinated by a range-extender and power battery with components decoupled by independent multi-motor driving. The mathematical models of SHECH operating components are established and the power system parameters are designed according to the operational requirements. Furthermore, the dynamic performance, performance of components and fuel economy of SHECH are analysed. Simulation results indicate that SHECH can recover 7.50% of battery state of charge during a single unloading operation, and the maximum operating area in pure electric mode is approximately 10,000 m2. This not only ensures operational performance but also effectively reduces fuel consumption. A hardware in the loop test was carried out to verify the power performance and the function of energy management system of SHECH. In addition, SHECH greatly simplifies the drive system and improves power transmission efficiency compared to conventional combine harvesters. Moreover, the function of independent operation of each component provides the basis for realising the speed adjustment of each key component as required. It provides a new idea for the research of improving harvester operation performance, and further expand space for strengthening the intelligence and adaptability of combine harvesters.

Unlocking the multi-mode energy-saving potential of a novel integrated thermal management system for range-extended electric vehicle

The thermal management system of range-extended electric vehicles (REEV) is essential for energy saving. There is a lack of modification methods for enhancing its performance under multiple operating modes. Herein, we present a combined cooling and power cycle-based basic integrated thermal management system (ITMS) for the REEV and propose a generalised performance improvement approach adapted to multiple operating modes. Composed of a waste heat recovery and a cooling subsystem, the basic ITMS can achieve heat recovery and thermal management of the range extender's coolant and recirculated exhaust gas and cools the passenger compartment and battery packs. The factors limiting the basic ITMS are identified through parametric analysis: the low evaporative pressures constrained by the low-temperature waste heat (engine coolant) and cooling target (passenger compartment). In order to unlock the multi-mode potential of the ITMS, we introduce the liquid-vapour separation condenser to separate the working fluid (zeotropic mixture) into two mixtures with different volatility. The high-volatility mixture is utilised to absorb the low-temperature engine coolant's waste heat and generate the low-temperature cooling energy for the passenger compartment, lifting evaporative pressures while keeping the condensation pressure unchanged. Then, a multi-mode comparison verifies the modified system. When the vehicle operates with the range extender on and with/without cooling demand, the vehicle fuel consumption rate can be reduced by 6.6% and up to 12.5%, respectively. When the vehicle runs in pure electric mode and with cooling demand, the ITMS's electrical consumption can be lowered by 7.4%. Accordingly, matching the volatility of the zeotropic working fluid and the thermal management objects enables REEV's ITMS to fulfil substantial energy savings in multiple operating modes.

An integrated thermal management strategy for cabin and battery heating in range-extended electric vehicles under low-temperature conditions

The integrated thermal management strategy under low-temperature conditions can effectively alleviate mileage anxiety associated with electric vehicles and improve the thermal comfort of the cabin. In this study, an integrated thermal management topology for range-extended electric vehicles is proposed, which recovers the waste heat from the range extender and the electric drive system for the heating of the battery and the cabin to improve energy utilization. Considering the driving modes and heating demands, the working modes and switching rules are designed. Especially, a control-oriented coupling system model is established for pure-electric mode. Taking cabin heat load demand, battery heat generation, and electric drive system heat generation as disturbances, a model predictive controller is designed for the heating power of the heater. An integrated thermal management system model verified by experiments is established in AMEsim. The initial temperature of the environment and vehicle is −20 °C, and the target temperatures of the cabin and the battery are set at 20 °C and 25 °C respectively. The feasibility of the strategy is verified by the co-simulation of Simulink and AMEsim under 4 WLTC cycles. The results show that in the range-extended mode, the integrated system shortens the battery heating time and reduces fuel consumption by more than 10.2 % compared with the independent system. In pure-electric mode, the heating speed of the proposed model predictive control strategy is slightly faster than that of the on–off strategy, the heating energy consumption is reduced by 20.95 %, and the total energy consumption for propulsion and thermal management decreased by 2.84 %.

An Offline Closed-Form Optimal Predictive Power Management Strategy for Plug-In Hybrid Electric Vehicles

This article develops an optimal predictive power management strategy (OP-PMS) for plug-in hybrid electric vehicles (PHEVs) to manage the remaining battery level throughout a defined journey. Apart from using the battery before charging it again at the destination, this approach also supports transit through an Ultra Low Emission Zone (ULEZ), where a PHEV needs to operate in pure electric mode to avoid emissions. This type of PHEV power management strategy (PMS) design problem is a noncausal control problem, where the power demand of the remaining driving cycle and the final battery energy level targets influence the current power management action. Rather than solving the whole optimization problem online, this article presents a simplification that leads to a closed-form analytic solution with parameters that can be computed offline. This article makes three key contributions. First, a novel input-linearization method is developed, which converts the OP-PMS into a convex quadratic programming (QP) problem that captures the essential model nonlinearities using an input transformation and a quadratic cost function. Second, the influence of future power demands and final targets on current energy management policy is explicitly quantified from a dynamic optimal control perspective. Third, the noncausal convex QP is approximated with a closed-form analytic solution that is calculated offline. This leads to a real-time implementable OP-PMS with coefficients that can be precalculated and stored in the engine control unit. To demonstrate the viability of this approach, numerical examples are provided based on a generic PHEV model to verify the efficacy of the proposed OP-PMS.

Deep reinforcement learning based energy management strategy for range extend fuel cell hybrid electric vehicle

To meet the power and long-range driving requirements of the vehicle, this paper presents a dual mode operation scheme for a range extend fuel cell hybrid vehicle for the first time, with an in-depth study of the pure electric mode and the range extend mode. The deep deterministic policy gradient algorithm is a well-known deep reinforcement learning algorithm that can solve complex nonlinear problems. To achieve the optimal power distribution among energy sources in the two modes, a dual deep deterministic policy gradient algorithm framework is proposed for the first time in this paper. In addition, a pervious action guidance mechanism is proposed to enable networks to approximate the action value function more efficiently in training. The training results show that the adopted previous action guidance mechanism helps to improve the learning convergence and exploration ability. The validation results show that the proposed strategy improves the operating economy by about 30% compared to the rule-based strategy, reduces the average fuel cell output fluctuation to less than 100 W, and reduces the fuel cell lifetime loss greatly. It is hoped that the proposed new structure, patterns, and energy management strategy will provide more ideas for scholars in future research.

Coordinated control strategy for mode switching of power-split hybrid electric bus

In the dynamic process of mode switching of the power-split hybrid electric bus, the vehicle will have longitudinal shock due to the drastic change of the two motors’ torque and the engine’s slow response. To solved this problem, this paper will focus on the process of switching from pure electric mode to hybrid drive mode, considered the operational state changes before and after engine ignition, limited the torque fluctuation transmitted from the front planetary set to the output shaft based on the idea of motor compensation, and calculated the motor compensation torque of the rear planetary set to compensate the torque fluctuation of the output shaft, to reduce the jerk. Firstly, the dynamic models of the transmission system before and after the engine ignition are established, respectively, and then the dynamic torque of the engine is estimated by XGBoost. The estimated value is input into the model predictive controller (MPC) to track the engine speed and calculate the torque fluctuation generated by the front planetary set on the output shaft. Then, according to the estimated value of the engine torque and the predicted value of the engine’s speed, the compensation torque is calculated by the sliding mode controller (SMC). Finally, the vehicle model is built with AVL CRUISE and MATLAB/Simulink software to verify the mode switching control effect of hybrid electric bus under typical urban conditions in China. The results showed that this control strategy significantly reduces the jerk of the mode switching process.

Numerical assessment of integrated thermal management systems in electrified powertrains

Temperatures in internal combustion engines (ICE) impact fuel consumption and pollutant emissions, especially under transient operating conditions. In hybrid powertrains, where the reciprocating internal combustion engine has intermittent operating conditions, a optimum control of these temperatures is critical. In this work, a detailed methodology for studying integrated thermal management systems for hybrid propulsion system was presented. Both experimental measurements and 0D/1D models were implemented and validated for the different components of the hybrid vehicle powertrain. The novelty of this work consists in the extensive experimental measurements involved for the development of the different models, specially the ICE, in order to study the integration of the different thermal flows of a hybrid powertrain. Furthermore, the simulation methodology used in this work integrates different modelling tools and takes advantage of their strengths when compared to using a single modelling tool. Two different thermal management systems have been evaluated under different Real Driving Emission (RDE) cycles at two different temperatures (at 20 °C and -20 °C). Results have shown that during the ICE warming up, the integrated thermal management system improved energy consumption by 1.74% and 3% for warm and cold conditions, respectively. This was because, the integrated TMS allows to avoid the temperature drop of the ICE when the propulsive system is in pure electric mode.

Real driving emissions of Euro 6 electric/gasoline hybrid and natural gas vehicles

Electric hybrid powertrain and natural gas fuel for spark-ignition engines are among the much promising technologies to reduce the fossil fuel use for road transportation and the emissions of harmful and greenhouse gases. This paper investigated gas and particulate real emissions of hybrid and natural gas passenger cars. On road testing were carried out along urban, rural and motorway routes in Napoli (Italy), by using portable emissions measurement systems. Hybrid vehicle has the main advantage of fuel saving in urban environment due to large use of pure electric mode operation at low speed and load. On the other hand, continuous engine restarting causes peak emissions due to a longer light-off time of aftertreatment systems. By analysing the Vehicle Specific Power, it was observed that at same positive values of power, natural gas vehicle is characterized by lower emission and fuel/energy consumption rates compared to the hybrid vehicle.

Hybrid Electric AWD Vehicle Kit

Abstract: The environmental impact of ICE automobiles in the late twentieth and early twenty-first centuries prompted the development of electric vehicles. Electric vehicles have numerous advantages over traditional internal combustion engines (ICE) vehicles, including the fact that they emit no carbon dioxide into the atmosphere. With many advantages of electric vehicles over traditional ICE vehicles, the world is moving toward EVs as a new improved means of transportation. Electric vehicles' tank to wheel efficiency is three times larger than ICE vehicles', and electric vehicles have very low running and maintenance costs. Even though electric vehicles are the best alternative, they do have significant disadvantages that are listed in the problem statement. Our proposal aims to bridge the gap between pure electric and traditional ICE automobiles by combining the primary benefits and advantages of both technologies. The project's main goal is to convert any existing ICE car into the most efficient vehicle possible. Our car can basically run on two distinct independent sources of energy, or even a combination of both. It can function as a pure electric vehicle, a pure ICE vehicle, or a hybrid AWD vehicle (where high amount of power is required). It has been shown that the average city dweller does not drive his or her car for more than 25 kilometers per day, and that the vehicle is parked the majority of the time. As a result, that individual can traverse that distance in pure electric mode, and our vehicle's solar charging mechanism will recover/recharge the energy expended while on the road. As a result, the person will be able to use our vehicle for free to generate sustainable energy. The use of ICE vehicles is rapidly increasing pollution in the environment; even pure EVs are an indirect source of pollution because the bulk of power is still generated by burning coal, thus our vehicle's use will undoubtedly make a significant difference.

Active Control of Torsional Vibration during Mode Switching of Hybrid Powertrain Based on Adaptive Model Reference

When the energy management and coordinated control of the hybrid electric vehicle power system are not proper, torsional vibration problems will occur in various working states, especially in the mode switching process. These vibrations will affect the comfort, economy and emission of vehicles. In order to suppress the torsional vibration, this paper studied the active vibration control algorithm for the hybrid powertrains under the switching process of pure electric mode to hybrid mode. Primarily, the clutch combination process was divided into five stages and the dynamic models of the transmission system of each stage were established, respectively. Moreover, the principle of model reference adaptive control was analyzed. The applicability of the method to the torsional vibration of the driveline during mode switching was described. Furthermore, the clutch free displacement phase was used as the reference model. A model reference adaptive torsional vibration controller was built based on the controlled model. Finally, the efficacy of this active method for vibration reduction was simulated. The simulation results show that torsional vibration is most likely to occur in the speed coordination stage and the full participation stage. In these two stages, the designed controller can reduce the fluctuation of motor speed by 93.2% and 97.5%, respectively, the engine speed by 79.6% and 77.4%, respectively, the motor acceleration by 96.7% and 82.3%, respectively, and the engine acceleration by 88.9% and 82.3%, respectively. In addition, the controller can reduce the impact degree of the transmission system to within ±1 m/s3.

Model predictive control for active vibration suppression of hybrid electric vehicles during mode transition

To realize a rapid and comfortable mode transition process from pure electric mode to hybrid mode (E-H), this study proposes an innovative control strategy which combines open-loop control with model predictive control to regulate the E-H process for a P2.5 configuration hybrid electric vehicle. Firstly, a detailed vehicle longitudinal dynamic model is established and the mode transition process is divided into four phases to reveal the control problems. Based on this model, a strategy combining open-loop control with model predictive control is developed. The open-loop control is adopted before the clutch is locked in order to speed up the transition process and limit the vehicle jerk. The model predictive control (MPC) is adopted after the clutch is locked to actively suppress the vibration caused by the abrupt change of clutch torque at the moment of clutch lock-up. Finally, simulation and hardware-in-the-loop test demonstrate that the proposed strategy for mode transition can achieve both switching rapidity and riding comfort. The algorithm robustness is also discussed and the signal transmission delay influence caused by controller area network (CAN) is studied.

Energy consumption of diesel hybrid electric bus simulated from different drive modes

The fuel and energy consumptions between different drive modes of the diesel hybrid electric bus were simulated and compared in this study. The simulated consumptions from two different hybrid modes were compared to the one obtained from the pure diesel mode and the pure electric mode. The backward simulation scheme was used to determine the required traction power of vehicles at specified vehicle velocity and time entire the driving cycle defined in the EPA heavy duty urban dynamometer driving schedule. The summation of fuel consumption of diesel engine, which was referred to the theoretical model of the diesel cycle, and the electric energy consumption of the motor were set as the total energy consumption at a certain specified time of the diesel hybrid electric bus. The conclusion showed that the combination of the drive mode with higher percentage of motorized power can reduce the summation of energy consumption and the energy cost of the diesel hybrid electric bus.

Analysis of the strategies for managing extended-range electric vehicle powertrain in the urban driving cycle

Introduction. An Extended-Range Electric Vehicle (EREV) is a type of electric vehicle that uses an additional internal combustion engine (ICE) to charge the battery in order to provide the vehicle with a greater range than in electric only mode. Purpose. Analysis and comparison of the performance of EREV powertrain managed according to three control strategies: pure electric mode, hybrid mode with ICE constantly working, and hybrid mode with ICE working only at high power demand. Methods. The tests were carried out using a laboratory test stand that represented the structure of EREV powertrain. Liquefied petroleum gas was used as a fuel to supply the ICE. The test conditions were defined by a special driving cycle simulating urban driving. Results. Time series plots of selected parameters of electric motor, electrochemical battery pack, range extender generator and active load system. Practical value. Among the considered control strategies of EREV powertrain, the energy balance of the electrochemical battery is negative for a purely electric mode, significantly positive for continuous range extenders (REXs) operation mode and moderately positive for the mode with REX activation only in dynamic states.

Adaptive torsional vibration active control for hybrid electric powertrains during start-up based on model prediction

Torsional vibration occurs when the hybrid vehicle transmission system is influenced by the multiple excitations and the dynamic loads caused by mode switching. Torsional vibrations of transmission system directly affect the stability, reliability, and safety of vehicles. In order to suppress the torsional vibration, this paper studied the active vibration control algorithm for the hybrid powertrains under rapid acceleration. Primarily, the architecture and the dynamic modeling of the drive system of the hybrid vehicle was built. Moreover, the hybrid control system including engine controller, motor controller and transmission controller was proposed. Furthermore, an adaptive active control controller was constructed to solve the torsional vibration problem. And model prediction control (MPC) and Butterworth filter control were combined into the controller. Finally, the efficacy of this active method for vibration reduction under start-up conditions was simulated. The simulation results showed that the torsional vibration of the transmission system was reduced by 96%–99% with external interference and the system stabilization time was advanced by 93% without external interference. The adaptive control algorithm suggested in this paper effectively suppressed the torsional vibration of hybrid electric vehicles (HEV) when accelerating in pure electric mode, without affecting vehicles’ dynamic performance.

Adaptive Mode Selection Strategy for Series-Parallel Hybrid Electric Vehicles Based on Variable Power Reserve

When the series-parallel hybrid electric vehicle exits the pure electric mode, the battery provides power for the drive motor and integrated starter generator (ISG) to drive the vehicle and start the engine. If the battery discharge power is insufficient, the driving power will drop, which will inhibit the vehicle from accelerating and impair drivability. Considering that the mode selection strategy determines the timing of mode switching, this paper proposes an adaptive mode selection strategy based on variable power reserve to allow the vehicle to switch mode considering the battery power limitation. The effectiveness of this strategy is verified by simulation, and its influence on fuel consumption and battery utilization is analyzed. Compared with the mode selection strategy based on logic thresholds at the same initial battery state of charge (SOC), under the high-speed and aggressive US06 cycle, the total driving power drop is reduced by 74.2%, and the over-discharge power of the battery is fully restrained while keep almost the same fuel consumption; under the city FTP cycle, the total driving power drop is reduced 65%, and fuel consumption is reduced while maintaining SOC at a reasonable level.

Control optimization of a compound power-split hybrid power system for commercial vehicles

In this paper, based on two planetary gear sets, a novel compound power-split hybrid power system for commercial vehicles is presented. Firstly, mathematical models of the system dynamic torque control and the system efficiency are established by using an equivalent lever diagram and analyzing the power flow respectively. Then the system operating modes which are divided into two pure electric modes and one hybrid mode and corresponding control strategies are analyzed by the combined lever diagrams. Finally, control strategies in different modes to looking for the optimal system efficiencies are designed and validated by the bench test. In order to prolong its service life, the battery is charged with small power in the hybrid mode. The design and test results indicate that the optimal system efficiency control strategies are reasonable and reliable. The maximum value of the optimal system efficiency can reach about 0.92 in the pure electric mode, and 0.39 in the hybrid mode. And the proportion of the engine operating points with the brake specific fuel consumption (BSFC) lower than 215 g/kWh is 81%. The co-simulation results show that the maximum system efficiency can achieve 14.9% fuel consumption per 100 km drop compared with the minimum system efficiency for an 80 km/h constant speed condition, which indicates that the optimal system efficiency control strategy can greatly improve the vehicle fuel economy. This study can offer a research direction for energy management of hybrid power systems.