Hybrid electric vehicles are an effective solution for reducing pollution and improving the fuel economy. Their control strategy often makes the vehicle control unit shut down and restart the internal-combustion engine for better fuel consumption. Starting and stopping the engine can cause driveline vibration, which is easily passed to the driver through the vehicle structure, causing ride discomfort. This research simulates the neutral start and stop of a two-mode hybrid system and correlates this with hardware tests. It investigates a pulse cancellation algorithm to cancel undesired vibration and to smooth ripples in the engine speed during automatic start–stop transitions. Electric motors provide torque to cancel unwanted torque impulses from uneven automatic starts or stops. This study also investigates the damper-bypass clutch. The results show that using pulse cancellation and the damper-bypass clutch can significantly reduce the reaction torque acting on the engine block and vibration of the seat track during automatic start–stop transitions.

This research focused on real-time optimization control to improve the fuel consumption of power-split hybrid electric vehicles. Particle swarm optimization (PSO) was implemented to reduce fuel consumption for real-time optimization control. The engine torque was design-variable to manage the energy distribution of dual energy sources. The AHS II power-split hybrid electric system was used as the powertrain system. The hybrid electric vehicle model was built using Matlab/Simulink. The simulation was performed according to US FTP-75 regulations. The PSO design objective was to minimize the equivalent fuel rate with the driving system still meeting the dynamic performance requirements. Through dynamic vehicle simulation and PSO, the required torque value for the whole drivetrain system and corresponding high-efficiency engine operating point can be found. With that, the two motor/generators (M/Gs) supplemented the rest required torques. The composite fuel economy of the PSO algorithm was 46.8 mpg, which is a 9.4% improvement over the base control model. The PSO control strategy could quickly converge and that feature makes PSO a good fit to be used in real-time control applications.

Targeting the application of medium and heavy vehicles, a hydraulic electric hybrid vehicle (HEHV) was designed, and its energy management control strategy is discussed in this paper. Matlab/Simulink was applied to establish the pure electric vehicle and HEHV models, and backward simulation was adopted for the simulation, to get the variation of torque and battery state of charge (SOC) through New York City Cycle of the US Environmental Protection Agency (EPA NYCC). Based on the simulation, the energy management strategy was designed. In this research, the rule-based control strategy was implemented as the energy distribution management strategy first, and then the genetic algorithm was utilized to conduct global optimization strategy analysis. The results from the genetic algorithm were employed to modify the rule-based control strategy to improve the electricity economic performance of the vehicle. The simulation results show that the electricity economic performance of the designed hydraulic hybrid vehicle was improved by 36.51% compared to that of a pure electric vehicle. The performance of energy consumption after genetic algorithm optimization was improved by 43.65%.

The use of hybrid electric vehicles is an effective means of reducing pollution and improving fuel economy. Certain vehicle control strategies commonly automatically shut down or restart the internal combustion engines of hybrid vehicles to improve their fuel consumption. Such an engine autostart/stop is not engaged or controlled by the driver. Drivers often do not expect or prepare for noticeable vibrations, noise, or an unsmooth transition when the engine is autostarted/stopped. Unsmooth engine autostart/stop transitions can cause driveline vibrations, making the ride uncomfortable and the customer dissatisfied with the vehicle. This research simulates the dynamic behaviors associated with the neutral starting and stopping of a power-split hybrid vehicle. The seat track vibration results of analysis and hardware tests of the baseline control strategy are correlated. Several antivibration control strategies are studied. The results reveal that pulse cancellation and the use of a damper bypass clutch can effectively reduce the fluctuation of the engine block reaction torque and the vibration of the seat track by more than 70% during the autostarting and stopping of the engine. The initial crank angle can have an effect on the seat track vibration as well.

Compared with conventional vehicles, hybrid electric vehicles (HEVs) have the advantage of high-energy conversion efficiency, which can have better fuel economy and lower emissions. The main issue of HEVs is how to develop an energy management strategy to achieve significantly better fuel efficiency. In this research, the Equivalent Consumption Minimization Strategy (ECMS) was applied to optimize the performance of fuel consumption in the Advanced Hybrid System-II (AHS-II). Based on FTP-75 Test Procedure defined by the U.S. Environmental Protection Agency (EPA), a backward simulation module was established. The baseline simulation module with the rule-based control strategy was validated with the original fuel consumption data. Then, the module with ECMS followed the same control rules of engine on/off and mode selection, and the fuel consumption of ECMS was compared with the simulation results of the baseline model. The fuel economy improvements of ECMS in urban, highway driving pattern, and composite fuel economy were up to 8.5%, 7.7%, and 8.1%, respectively. The simulation results showed that the difference of motors’ working efficiency was only 1.2% between ECMS and baseline rule-based control strategies. The main reason of fuel consumption improvement was the engine operation chosen by ECMS, which provided better power distribution.