Optimal Gear-Shifting of a Wet-Type Two-Speed Dual-Brake Transmission for an Electric Vehicle

In improving the efficiency of powertrain systems and ride comfort for electric vehicles (EVs), the transmission model is required to enable more accessible and more straightforward control of such vehicles. In this study, a wet-type, two-speed, dual-brake transmission system, as well as a new electromechanical clutch actuator, is presented for EVs. A new coordinated optimal shifting control strategy is then introduced to avoid sharp jerks during shifting processes in the transmission system. Based on a state-space model of the electromechanical clutch actuator and dual-brake transmission, we develop a linear quadratic regulator strategy by considering ride comfort and sliding friction work to obtain optimal control trajectories of the traction and shifting motors under model-based control. Simulations and bench tests are carried out to verify the performance of the proposed control laws. Results of the proposed coordinated control strategy show that noticeable improvements in terms of vehicle jerk and friction energy loss are achieved compared with an optimal control scheme only for the shifting motor as the input

Evaluating Accessibility Benefits of Opening Gated Communities for Pedestrians and Cyclists in China: A Case Study of Shanghai

Opening gated communities (GCs) has been widely discussed for urban inclusion and revitalization. With the policies of opening GCs being promoted in China, the quantitative and comprehensive evaluation of the potential benefits is heavily needed. Taking Shanghai as an example, this study quantifies and analyzes the accessibility benefits and risks of opening GCs for pedestrians and cyclists considering two GC types, two opening levels, two travel modes, and different facilities. We found that (1) opening GCs can bring 50 m+ accessibility gains to 17% and 52% of the residents in moderate opening (MO) and complete opening (CO) scenarios, respectively. (2) Cyclists benefits more than pedestrians in all scenarios. (3) Conventional GCs have fewer benefits in MO but more in CO than newly established ones. Trips to bus stations demonstrate the largest accessibility gains. (4) The accessibility benefit of a residential building is highly determined by its closeness to the gates and relative location in the block. (5) Only 1% and 5–7% of external trips may penetrate the opened communities in MO and CO scenarios, respectively, which are far less than both the expectation and the benefits. Finally, several local design guidelines are proposed

Evaluating Accessibility Benefits of Opening Gated Communities for Pedestrians and Cyclists in China: A Case Study of Shanghai

Opening gated communities (GCs) has been widely discussed for urban inclusion and revitalization. With the policies of opening GCs being promoted in China, the quantitative and comprehensive evaluation of the potential benefits is heavily needed. Taking Shanghai as an example, this study quantifies and analyzes the accessibility benefits and risks of opening GCs for pedestrians and cyclists considering two GC types, two opening levels, two travel modes, and different facilities. We found that (1) opening GCs can bring 50 m+ accessibility gains to 17% and 52% of the residents in moderate opening (MO) and complete opening (CO) scenarios, respectively. (2) Cyclists benefits more than pedestrians in all scenarios. (3) Conventional GCs have fewer benefits in MO but more in CO than newly established ones. Trips to bus stations demonstrate the largest accessibility gains. (4) The accessibility benefit of a residential building is highly determined by its closeness to the gates and relative location in the block. (5) Only 1% and 5–7% of external trips may penetrate the opened communities in MO and CO scenarios, respectively, which are far less than both the expectation and the benefits. Finally, several local design guidelines are proposed

Gear Ratio Optimization of a Multi-Speed Transmission for Electric Dump Truck Operating on the Structure Route

Research demonstrated that the application of a multi-speed transmission could improve the dynamic and economic performance of electric vehicles. This paper deals with a novel multi-speed transmission for the electric dump truck (EDT) operating on the structure route (SR), which has a definite starting point and end point without complex traffic conditions. To optimize the gear ratio and shift schedule to reduce energy consumption in such conditions, the mathematical model of the transmission and the dynamic model of the EDT are initially required. Following this, the shift schedule is presented according to the motor efficiency map. After that, the gear ratio optimization is carried out by a particle swarm optimization (PSO) algorithm. Moreover, the proposed EDT is compared with an EDT with a single-speed transmission. The simulation results show that the energy consumption is reduced by 6.1%

Cascade Direct Yaw Moment Control for an Independent Eight In-Wheel Motor-Driven Autonomous Vehicle

Unstructured off-road environments with complex terrain obstacles and pavement properties bring obvious challenges for special purpose autonomous vehicle control. A cascade direct yaw moment control strategy (CDYC), which contains a main loop and a servo loop, is proposed to enhance the accuracy and stability of an independent eight in-wheel motor-driven autonomous vehicle with rear-wheel steering (8WD/RWS). In the main loop, double PID controllers are designed to generate the desired drive moment and yaw rate. In the servo loop, the quadratic programming (QP) algorithm with the tire force boundaries optimally allocates the demanded yaw moment to individual wheel torques. The 8WD/RWS prototype is virtually established using TruckSim and serves as the control object for co-simulation. The proposed cascade controller is verified by simulations in customized off-road driving scenarios. The simulation results show that the proposed control architecture can effectively enhance the path-tracking ability and handling stability of the 8WD/RWS, as to ensure the maneuverability and control stability under extreme off-road conditions

Cascade Direct Yaw Moment Control for an Independent Eight In-Wheel Motor-Driven Autonomous Vehicle

Unstructured off-road environments with complex terrain obstacles and pavement properties bring obvious challenges for special purpose autonomous vehicle control. A cascade direct yaw moment control strategy (CDYC), which contains a main loop and a servo loop, is proposed to enhance the accuracy and stability of an independent eight in-wheel motor-driven autonomous vehicle with rear-wheel steering (8WD/RWS). In the main loop, double PID controllers are designed to generate the desired drive moment and yaw rate. In the servo loop, the quadratic programming (QP) algorithm with the tire force boundaries optimally allocates the demanded yaw moment to individual wheel torques. The 8WD/RWS prototype is virtually established using TruckSim and serves as the control object for co-simulation. The proposed cascade controller is verified by simulations in customized off-road driving scenarios. The simulation results show that the proposed control architecture can effectively enhance the path-tracking ability and handling stability of the 8WD/RWS, as to ensure the maneuverability and control stability under extreme off-road conditions

Research on Vehicle Active Steering Stability Control Based on Variable Time Domain Input and State Information Prediction

The controller design of vehicle systems depends on accurate reference index input. Considering information fusion and feature extraction based on existing data settings in the time domain, if reasonable input is selected for prediction to obtain accurate information of future state, it is of great significance for control decision-making, system response, and driver’s active intervention. In this paper, the nonlinear dynamic model of the four-wheel steering vehicle system was built, and the Long Short-Term Memory (LSTM) network architecture was established. On this basis, according to the real-time data under different working conditions, the information correction calculation of variable time-domain length was carried out to obtain the real-time state input length. At the same time, the historical state data of coupled road information was adopted to train the LSTM network offline, and the acquired real-time data state satisfying the accuracy was used as the LSTM network input to carry out online prediction of future confidence information. In order to solve the problem of mixed sensitivity of the system, a robust controller for vehicle active steering was designed with the sideslip angle of the centroid of 0, and the predicted results were used as reference inputs for corresponding numerical calculation verification. Finally, according to the calculated results, the robust controller with information prediction can realize the system stability control under coupling conditions on the premise of knowing the vehicle state information in advance, which provides an effective reference for controller response and driver active manipulation