Conventional vehicles tend to consume considerable amounts of fuel, which generates exhaust gases and environmental pollution during intermittent driving cycles. Therefore, prospective vehicle designs favor improved exhaust emissions and energy consumption without compromising vehicle performance. Although pure electric vehicles feature high performance and low pollution characteristics, their limitations are their short driving range and high battery costs. Hybrid electric vehicles (HEVs) are comparatively environmentally friendly and energy efficient, but cost substantially more compared with conventional vehicles. Hydraulic hybrid vehicles (HHVs) are mainly operated using engines, or using alternate combinations of engine and hydraulic power sources while vehicles accelerate. When the hydraulic system accumulator is depleted, the conventional engine reengages; concurrently, brake-regenerated power is recycled and reused by employing hydraulic motor–pump modules in circulation patterns to conserve fuel and recycle brake energy. This study adopted MATLAB Simulink to construct complete HHV and HEV models for backward simulations. New European Driving Cycles were used to determine the changes in fuel economy. The output of power components and the state-of-charge of energy could be retrieved. Varying power component models, energy storage component models, and series or parallel configurations were combined into seven different vehicle configurations: the conventional manual transmission vehicle, series hybrid electric vehicle, series hydraulic hybrid vehicle, parallel hybrid electric vehicle, parallel hydraulic hybrid vehicle, purely electric vehicle, and hydraulic-electric hybrid vehicle. The simulation results show that fuel consumption was 21.80% lower in the series hydraulic hybrid vehicle compared to the series hybrid electric vehicle; additionally, fuel consumption was 3.80% lower in the parallel hybrid electric vehicle compared to the parallel hydraulic hybrid vehicle. Furthermore, the hydraulic–electric hybrid vehicles consumed 11.4% less electricity than the purely electric vehicle did. The simulations indicated that hydraulic-electric hybrid vehicle could provide the best energy cost among all the configurations studied.

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%.

Electric vehicles have replaced many gasoline vehicles in urban environments. The magnitude of vibrations and emissions from electric vehicles are less than those from conventional gasoline-powered vehicles. However, electric vehicles still have mechanical vibrations, such as those created by the power system. During vehicle acceleration, driveline vibration is very prominent. This work focuses on vehicle vibration caused by the electric powertrain in electric vehicles under rapid acceleration/deceleration and gear shifting. Since the dynamic response of an electric motor is rapid, driving torsional vibration arising from acceleration/deceleration and gear shifting is typically transmitted from driveline to vehicle’s body, adversely affecting a driver’s comfort. This work presents a novel effective control logic that reduces vibrations from an electric driveline system. This system controls the electric motor to suppress driveline torsional vibration transmitted to the driver’s seat, effectively reducing vertical vibrations and enhancing driver comfort. This work conducts simulations and hardware tests. In the development of the driveline and motor control logic, Adaptive Modeling Environment for Simulation analytical software is applied to create the driveline system model. To model structural vibrations, HyperMesh is used, and LS DYNA is applied to simulate free vibration and forced vibration. The analytical results for free vibration are compared with empirical data. The analytical results for driveline dynamics are applied as input for the finite element model to analyze forced vibration. Vibrations from the electric driveline move through the motor mount and frame to the driver’s seat track. The simulation results demonstrate this control logic strategy applied to an electric bus motor controller effectively reduces fluctuation in driveline torque during acceleration by up to 84.19% and during gear shifting by up to 44.96%. The reduction in vibration of the driver’s seat track during fixed-gear acceleration was maximal at 45.96%, and the reduction during gear shifting was 24.11%.

Electric vehicles are a major trend in research and development in the automobile industry. A vehicle’s handling ability is changed when the structure of the power system is altered, which is more obvious in medium-sized buses with higher load and a longer body whose body stiffness is relatively less stiff. In this context, flexible multi-body dynamic modeling, instead of rigid body modeling, is used to reflect the stiffness effects of the vehicle body and chassis systems. A control strategy is developed with an active variable stiffness anti-roll bar to improve vehicle handling characteristics by using the flexible body dynamic simulation with consideration of the step and single sinusoidal steering input tests. Through simulation, it was learned that the proposed control strategy could reduce the time of stabilization by 54.08% and suppress undesired handling behaviors in the step steering input test. Moreover, at high speed, the original unsteady condition became stabilized with little sacrifice in yaw velocity. In the single sinusoidal steering input test, the time of stabilization could be reduced by 8.43% and with 14.6% less yaw angle changes in the improved design. The overall handling was improved.

In order to achieve better performance of fuel consumption in hybrid vehicles, the internal combustion engine is controlled to operate under a better efficient zone and often turned off and on during driving. However, while starting or shifting the driving mode, the instantaneous large torque from the engine or electric motor may occur, which can easily lead to a high vibration of the elastomer on the driveline. This results in decreased comfort. A two-mode power-split hybrid system model with elastomers was established with MATLAB/Simulink. Vibration reduction control strategies, Pause Cancelation strategy (PC), and PID control were developed in this research. When the system detected a large instantaneous torque output on the internal combustion engine or driveline, the electric motor provided corresponding torque to adjust the torque transmitted to the shaft mitigating the vibration. To the research results, in the two-mode power-split hybrid system, PC was able to mitigate the vibration of the engine damper by about 60%. However, the mitigation effect of PID and PC-PID was better than PC, and the vibration was able to converge faster when the instantaneous large torque input was made. In the frequency response, the effect of the PID blocking vibration source came from the elastomer was about 75%, while PC-PID additionally reduced 8% by combining the characteristics of the two control methods.