Reference velocity (i.e. the absolute velocity of vehicle center of mass) is a key parameter for vehicle stability functions such as the traction control system, anti-lock brake system, acceleration slip regulation, etc. It’s also a key parameter for longitudinal drive control functions of hybrid electric vehicle (HEV) such as the energy management, powertrain mode/gear shifting, drive and regenerative torque control, etc. Most reference velocity estimation methods employ the vehicle kinematics and tire dynamics equations to construct high order linear or quasi-linear system model with a set of parameters and sensor signals. When using those models, delicate estimation algorithm should be designed since the estimates tend to deviate along with the increase of nonlinearity, uncertainty and noise that introduced by high order, number of parameters and sensors, respectively.
In this paper, we propose a novel Split Ring Resonator (SRR) metamaterial capable of achieving a total bandgap in the material’s band structure, thereby reflecting air-borne and structure-borne noise in a targeted frequency range. Electric Vehicles (EVs) experience tonal excitation arising from the switching frequencies associated with motors and inverters, which affects occupant perception of vehicle quality. Recently proposed metamaterial designs isolate either air-borne noise or structure-borne noise, but not both. To achieve isolation of both air-borne and structure-borne acoustic energy associated with these tonal frequencies, we propose a metamaterial supercell with transverse and longitudinal resonant frequencies falling in the desired bandwidth of the total bandgap. We calculate the resonant frequencies and corresponding mode shapes using Finite Element (FE) modal analysis.
It is necessary for us to reduce CO2 emissions in order to hold down global warming which is advancing year by year. Toyota believes that it is important not only to introduce BEVs but also to promote technological development of HEVs and PHEVs in order to widely reduce CO2 emissions around the world. This time, we have developed a PHEV system for Prius. The traction battery Pack structure, the transaxle and the power control unit (PCU) with boosting converter system were newly developed based on the 2.0L hybrid system, resulting in 1.5 times the battery capacity with the almost same battery pack size and transmission efficiency has also been improved, extending EV distance by 70% from previous Prius. In terms of power, by adopting Double-Boost converter system and increasing the motor output, the system output power has been increased by 1.8 times with almost the same size as the previous unit.
DHT hybrid transmission assembly control system discussed in this paper includes hydraulic control, drive mode switching control, shift control, dual motor control, clutch and motor thermal management. Hydraulic control includes torque-pressure conversion. Including clutch pressure kp adaption, clutch gain adaption, clutch oil filling time adaption. Shift control includes shift type decision, shift timing control, shift torque exchange process control, shift inertia process based on motor intervention. Thermal management includes clutch flow and motor flow distribution. Motor control include the current control, mode control and boost strategy of permanent magnet synchronous motor in dual hybrid system, which has good stability and robustness. Current control includes current vector control, MTPA control, flux weakening control, PI current control and SVPWM control.
The rapid evolution of electric vehicle (EV) development has highlighted the need to develop EVs that meet customer demands for both high-performance and space-efficiency. This paper delves into the optimization opportunities available within the landscape of EV powertrains, focusing on the power-dense potential of single-axis powertrain systems. The need to adhere to power density requirements to accommodate performance aspirations while simultaneously yielding more cabin or storage space to the customer creates a challenging problem for designers. With this pursuit, these competing interests must strike a harmonious balance in order to create the best experience for the customer. The subject of this study is an investigation into a leading competitor's powertrain that explores the potential optimization opportunities available within its already compact single-axis electric transmission.
Recently, as part of the purpose of improving fuel efficiency and cost reduction of eco-friendly vehicles, the R-gearless system has been applied in TMED (P)HEV system It is necessary to develop a separate backward driving method as the reverse gear is removed, so backward driving can be enabled by using the e-Motor system in TMED (P)HEV system. However, backward driving with e-Motor is limited as partial failure of high-voltage system in R-gearless system Here we show that, it is possible to improve the backward driving problems by applying new fail-safe strategy. In the event of a high voltage battery system failure, the backward driving is available by using e-Motor with constant voltage control by HSG as we proposed in this paper. So feed-forward compensation of variable constant voltage control enables to secure more active output power within limited HSG output power.
Multi-motor powertrain topologies are playing an increasingly important role in the development of heavy duty battery electric trucks due to the changing driving requirements of these vehicles. The use of multiple motors and/or transmissions in a powertrain provides additional degrees of freedom for the energy management. The energy management system (EMS) consist of the gear selection strategy and torque split between the drive motors. The aim of the EMS is thereby to achieve high energy efficiency in motor and regenerative operation, while reducing the number of gear changes to ensure driving comfort. Ongoing research focuses on the energy management system of hybrid electric trucks, where the aim is to optimize the torque split between the combustion engine and the electric motor. In this paper, the EMS for an electric truck is described as a mixed-integer nonlinear control problem. This type of optimal control problem is notoriously difficult to solve.
This paper presents a feedback control strategy to minimize noise during dog clutch engagement in a hybrid transmission. The hybrid transmission contains an internal combustion engine(ICE) and 2 electric motors in P1 and P3 configurations. For efficiency during driving, at high vehicle speeds ICE is connected to wheels, via the dog clutch, hence shifting the vehicle from series to parallel hybrid mode. It is shown by experimental results that if the speed difference between the two sides of the dog clutch is below a certain level the engagement will be without clonk noise. In this paper the designed state feedback Linear Quadratic Integral (LQI) control provides the synchronization torque request to the P1 motor, hence matching the speed of one side of dog clutch with the other under the disturbance from combustion torque of the engine.
By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy in advance, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after separating the driver from the decision-making process, the current shift strategy is limited to the current vehicle state and cannot effectively determine the road environment ahead. There may be a problem of cyclic shifting due to insufficient power when driving on a slope. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.
The automatic transmission of a specialized vehicle experienced the issue of unstable oil charge time due to the significant variability of related parameters and the non-linear trend of individual product parameter changes over time. To investigate the underlying causes of this phenomenon and the improved oil charge effect, a detailed model of the clutch oil charge process during gear shifting was established in this paper, which included dynamic models of components such as the hydraulic system, clutch, proportional valve, and pumps. The influence of parameters such as orifice diameter, piston gap, and oil filling flow rate on the system response was taken into account. Dynamic simulations were conducted to study the impact of these parameters on the clutch oil charge time. Additionally, physical experiments were performed using a test bench to provide a comparison with the simulation results.
The Time-Sensitive Networking (TSN) working group has introduced a comprehensive set of standards to enable reliable communication in time-critical systems. The TSN standards set encompasses several shaping mechanisms that aim to provide bounded transmission latency for streams in the network. Among these shaping mechanisms, Cyclic Queuing and Forwarding (CQF) and frame preemption provide deterministic guarantees for frame transmission. However, despite some current studies on the performance analysis of CQF and frame preemption, they also need to consider the potential effects of their combined usage on frame transmission. Furthermore, there is a need for more research that addresses the impact of parameter configuration on frame transmission under different situations and shaping mechanisms, especially in the case of mechanism combination.