Gear Shifting Control Strategy Research Articles

Surrogate-assisted multi-objective optimization for control parameters of adjacent gearshift process with multiple clutches

The limited sensors in mass-produced automatic transmissions introduce a significant challenge for performing gearshifts with multiple clutches. To tackle this challenge, this study proposes an integrated surrogate-assisted multi-objective optimization (ISAMO) framework to obtain the optimal control profiles. An optimization-oriented gearshift control strategy coordinated with engine torque reduction is proposed for the gearshift process with four active clutches. A multi-objective optimization problem is formulated to determine the optimal parameters of the proposed control strategy. To mitigate the excessive computation required by the iterative simulation of the physical model in the multi-objective optimization process, we construct a surrogate model to substitute for the physical model based on a radial basis function neural network (RBFNN) and an adaptive sampling method. The RBFNN surrogate model is used in conjunction with the non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto optimal set. The improved radar chart evaluation method is adopted to determine an optimal trade-off solution in the Pareto optimal set. The shift transitions of the optimal trade-off solution are simulated and analyzed. Results validate the effectiveness of the proposed ISAMO framework in improving optimization efficiency without sacrificing accuracy.

Novel shift process control strategy for two-speed clutchless automatic mechanical transmission based on segmented speed regulation

Battery electric vehicles (BEV) equipped with two-speed automatic mechanical transmission (AMT) have gained increasing popularity owing to advantages of a widened high-efficiency operation zone and system costs. In this study, a combined gear shift control strategy including a segmented speed regulation control and torque recovery control was developed for a two-speed AMT in BEV. The switching point of proportional integral control and sliding mode control during speed regulation process is adaptively optimized to ensure minimization of the shift time, while the maximum vehicle jerk is controlled within a defined range. The effectiveness of proposed control strategy is verified by a test bench. Results show that proposed control strategy can not only ensure the impact degree fluctuates within a predetermined range, but also achieve fast and accurate speed regulation which can reduce the speed regulation time by 17%–33%.

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.

Gear downshift control of inverse-automatic mechanical transmission of electric vehicle

In order to improve the driving dynamics and riding comfort of pure electric vehicles, taking a two-speed I-AMT (Inverse-Automatic Mechanical Transmission) with rear friction clutch as the research object, a gear shift strategy, which consists of the open-loop control of the clutch position control and the closed-loop control of the drive motor speed control, is proposed. Considering the inherent time-delay and external disturbances within the motor speed adjustment system, a two DOF (degree-of-freedom) Smith predictor with feedforward input is designed to track the target speed of the drive motor. The feedforward input is used to eliminate the influence of clutch sliding friction on the motor speed control, while the feedback speed tracking controller is applied to realize the speed tracking performance with the existence of time-delay and the external disturbance. In order to verify the effectiveness of the gear shift control strategy and the accuracy of the two DOF Smith controller with feedforward control, simulation results comparison is firstly carried out to illustrate the effectiveness of the control scheme. Then, a light pure electric vehicle equipped with I-AMT was used for downshift experiments under large throttle, which is the most difficult working scenario to control the transmission. The experimental results show that the two DOF Smith controller can eliminate the influence of time-delay on the closed-loop control, and the proposed whole gear shift control strategy can limit the clutch slippage time within 1.5 s, resulting in a smaller shift jerk, thus guarantee the driving dynamics and riding comfort simultaneously.

Power on gear shift control strategy design for a parallel hydraulic hybrid vehicle

The power on gear shift control of a parallel hydraulic hybrid vehicle (PHHV) is researched in this paper. A multibody dynamic model is built to capture the main vibration characteristics of PHHV powertrain, based on which the power on gear shift control strategy is designed and verified. To avoid the vehicle driving torque interruption during gear shift, power on gear shift control strategy is designed. In the control strategy, hydraulic pump/motor (HPM) compensates the engine torque when the engine clutch is disengaged for gear shift. The engine clutch engagement process is carefully controlled by LQR control strategy to mitigate the vehicle powertrain vibration and improve the vehicle driving comfort. Extended Kalman filter (EKF) is adopted to estimate the PHHV parameters required by LQR control. The available HPM torque depends on its working pressure which varies a lot with different accumulator state of charge. So the HPM torque compensation capability is investigated by analysing the traction force requirement during gear shift. To obtain the gear shift traction force demand, a gear shift schedule considering both vehicle fuel economy and dynamic performance is designed. The simulation results show that the HPM could satisfy most of the torque compensation requirements during gear shifts with the designed gear shift schedule in typical driving cycles.

Coordinate Receding Horizon Control for the Power-Shift Process of Multispeed Electric Vehicles

Given that electric motors are speed controllable in a wide range of operating speeds, achieving integrated control of the powertrain system is a good idea for improving shift quality and efficiency. This study proposes a coordinate optimal gearshift control strategy for EVs with a two-speed transmission, where the motor torque control is introduced in a clutch slip process. Where the motor torque and clutch push force signal are selected as optimization controller inputs. The contradictive performance objectives (power performance, smooth performance, less losses) are regarded as the optimal goals; moreover, the variable horizon MPC is presented to ensure that clutch engagement is completed within a specified time. Considering swift shifting requirements, a fast solution based on the minimum principle and dichotomy method is applied. Finally, based on a developed simulation model of an electric vehicle, the offline simulation is used to evaluate the effectiveness and real-time performance of the proposed coordinate optimal controller.

Coordinated control of gear shifting process with multiple clutches for power-shift transmission

In this work, a novel power-shift transmission is designed to achieve high transmission efficiency, reasonable gear distribution, and high fuel economy with relatively low processing difficulty and low manufacturing cost. Moreover, the parameters of this transmission are designed based on work requirements and the relative service time of each speed range during the life cycle of a tractor. Since gear shifts between some gears require a change in the states of four clutches, this process is very complex. In order to ensure the gear shifting quality and continuous power flow to driving wheels, the powertrain dynamical model is established, the power-on gear shifting processes are analyzed, and the coordinated control strategies are developed for upshift and downshift processes with changing multiple clutches during tractor field work. The effectiveness of the gear shifting control strategy is verified using the proposed simulation model. The results show that the coordinated control strategies ensure excellent power continuity, smoothness, and responsiveness for power-on upshift and power-on downshift processes with changing multiple clutches.

Five-parameter Shift Strategy of Automatic Mechanical Transmission for Electric Bus

According to optimized shift strategy, the electric vehicle equipped with automatic mechanical transmission (AMT) can make the driving motor running in high efficient working area, which can improve dynamic and economic performance for the vehicle in different driving conditions. Drivers, vehicles and roads are indivisible unity. How to identify driving intentions and road environment is the basis for intelligent automatic shifting system to achieve adaptive gear decision and shift control strategy. This paper proposed an algorithm using recursive least squares method to identify vehicle quality and road slope, and calculated a five-parameter shift strategy based on vehicle speed, throttle opening, mass, slope and acceleration which can make the vehicle have ideal economic performance while taking the power demand into consideration.

Advanced shifting control of synchronizer mechanisms for clutchless automatic manual transmission in an electric vehicle

On the basis of improving drivability and efficiency, an electric vehicle equipped with automatic manual transmission is a considerable framing. However, the conventional geared transmissions usually install automated clutch which require the hydraulic power in addition to the slippage in the clutch plate invoking some energy loss as well as wear. For this reason, a practical approach with respect to clutchless automatic manual transmission (CLAMT) and its gear-shifting control strategy for an electric vehicle was proposed by our research team. In order to determine the key factors affecting the gear-shifting operation of CLAMT, a dynamic model of the CLAMT driveline was developed and the dynamic characteristics of the transmission synchronizer during each gear-shifting phase were analyzed in this paper. The analysis indicates that the gear-shifting operation of CLAMT not only requires a power motor with the capability of rapid mode-switching and precise speed regulation, but also demands that the shift actuators have the ability of exact position adjustment and strong robustness against shift load variations. To realize rapid and accurate gear-shifting control, the key technique relating to the robust position control scheme for the gear-shifting actuators were described in detail and validated on a designed CLAMT test rig.

Automatic Gear Shifting in Sport Motorcycles

Performing safe and effective gear shifts on two-wheeled vehicles in an automatic way is a challenging task, mainly due to the complexity of the system dynamics and the safety-critical aspects of the application. This work offers one of the first contributions in this area, analyzing all the aspects related to this control problem. Specifically, this work provides two main results: an objective quality assessment of the gear-shifting performance and a new gear shift control strategy that optimizes the tradeoff between duration and comfort. The results obtained on an instrumented vehicle confirm the suitability of the proposed approach.

Powerful Gear Shifting Control for Hybrid Electric Bus with Automated Manual Transmission

Traditionally a gear shift with clutch and synchronizer control makes the synchronisation phase unnecessarily long torque gap time. Based on the benefit of a single shaft parallel hybrid electric bus (PHEV), fast gear shifting and reducing the shafts speed oscillation can be realized by controlling the electric machine with Model Predictive Control (MPC ) method instead of sliding the clutch and synchronizer to a torque-free state in the transmission. Detailed mathematical models of different driveline states are presented and to improve driving comfort. Theoretical and simulation analysis results are compared with experimental ones from the road experiment in equal conditions in order to prove the validity of the gear shifting control strategy.

Gear Shifting Control for Pure Electric Vehicle with Inverse-AMT

In this study, the gear shifting control strategy for pure electric vehicle with inverse automated manual transmission (I-AMT) is proposed. Based on a new drive train system of pure electric vehicle, an AMESim model of vehicle drive-train system is set up. Through the precise control of sliding sleeve, clutch engagement and separating time, gear shifting process is realized without driving torque interruption. The results show that, during up and down shift process, the driving torque keeps more than 50%, obviously improve the pure electric vehicle accelerating performance and the ability to climb.

Gear Shifting Control for Medium Truck without Clutch

Traditionally a gear shift with clutch control makes the synchronisation phase unnecessarily long torque gap time. Gear shifting by engine control realizes fast gear shifts by controlling the engine instead of sliding the clutch to a torque-free state in the transmission. Detailed mathematical models of different driveline states are presented and to improve driving comfortable. Theoretical analysis results are compared with experimental ones from the road experience in equal conditions in order to prove the validity of the gear shifting control strategy.

Gearshift control for automated manual transmissions

A gearshift control strategy for modern automated manual transmissions (AMTs) with dry clutches is proposed. The controller is designed through a hierarchical approach by discriminating among five different AMT operating phases: engaged, slipping-opening, synchronization, go-to-slipping, and slipping-closing. The control schemes consist of decoupled and cascaded feedback loops based on measurements of engine speed, clutch speed, and throwout bearing position, and on estimation of the transmitted torque. Models of driveline, dry clutch, and controlled actuator are estimated on experimental data of a medium size gasoline car and used to check through simulations the effectiveness of the proposed controller.