Pub Date : 2024-08-23DOI: 10.1177/09544070241272767
Anikrishnan Mohanan, Kannan Chidambaram
The paradigm shift from conventional to electric propulsion has become one of the pivotal foci of research areas. In the electric vehicle domain which encompasses a range of vehicles from two-wheelers to multi-wheelers, the battery thermal management system and its design variations are receiving the utmost attention. This article explores an array of distinct cooling strategies viz. evaporative, refrigeration assisted, mist, vapour chamber, thermoelectric and MEMS membrane cooling for lithium-ion batteries with their specifications, prominent attributes, advantages, limitations and thermal mitigating measures with potential future possibilities for electric two-wheelers. Grey relational analysis (GRA) is adopted to rank the cooling schemes disclosed that mist cooling is the most optimal for electric two-wheelers and this recommendation is substantiated with a numerical approach. The numerical results unveiled that the multi-strategical approach of mist cooling and forced convection attenuated the peak cell temperature by 13% and 24% when compared to stand-alone mist cooling and the system without external cooling assistance. This stands as evidence for the increased effectiveness of multi-strategical approaches. The article would help in creating the most practical combinational cooling solutions to lessen the danger of a thermal runaway with lithium-ion batteries, in particular, implemented in electric two-wheelers.
{"title":"Synergistic thermal management of lithium-ion batteries in electric two-wheelers: Critical analysis and ranking of multifaceted strategies and numerical validation","authors":"Anikrishnan Mohanan, Kannan Chidambaram","doi":"10.1177/09544070241272767","DOIUrl":"https://doi.org/10.1177/09544070241272767","url":null,"abstract":"The paradigm shift from conventional to electric propulsion has become one of the pivotal foci of research areas. In the electric vehicle domain which encompasses a range of vehicles from two-wheelers to multi-wheelers, the battery thermal management system and its design variations are receiving the utmost attention. This article explores an array of distinct cooling strategies viz. evaporative, refrigeration assisted, mist, vapour chamber, thermoelectric and MEMS membrane cooling for lithium-ion batteries with their specifications, prominent attributes, advantages, limitations and thermal mitigating measures with potential future possibilities for electric two-wheelers. Grey relational analysis (GRA) is adopted to rank the cooling schemes disclosed that mist cooling is the most optimal for electric two-wheelers and this recommendation is substantiated with a numerical approach. The numerical results unveiled that the multi-strategical approach of mist cooling and forced convection attenuated the peak cell temperature by 13% and 24% when compared to stand-alone mist cooling and the system without external cooling assistance. This stands as evidence for the increased effectiveness of multi-strategical approaches. The article would help in creating the most practical combinational cooling solutions to lessen the danger of a thermal runaway with lithium-ion batteries, in particular, implemented in electric two-wheelers.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-04DOI: 10.1177/09544070241266872
Amine Beloufa
Power automotive connectors used to connect two electrical systems in an electric vehicle should resist the rising of electric power or electric current. The latter can cause a rise in contact temperature by the Joule effect and can damage a connector improperly designed. The purpose of this work is to study experimentally and numerically the influence of the addition of a second spring on the ability of a power connector to transmit a high current. For this reason, an experimental test has been held on a connector without a second spring to measure contact resistance and contact temperature; then, a finite element model FEM of this connector was developed to compare and validate the numerical results with the experimental results. In addition, another FE model with a second spring was used to minimize contact resistance and contact temperature. Moreover, a theoretical model has shown its effectiveness in contact temperature and contact area calculations; it provides good agreement with experimental and numerical results. Numerical results show that the effect of the addition of a 2nd spring on the decrease of the contact temperature and contact resistance is significant. In addition, the thermo-electrical analysis by finite element shows that the current limit supported by a power connector with an auxiliary spring will equal twice the current supported by a power connector with one spring. FE mechanical analysis shows that the maximum mechanical stress in the connector with an auxiliary spring remains lower than the 2nd spring material yield stress. Finally, experimental and numerical results are in good agreement.
{"title":"The effect of an auxiliary spring on the decrease of contact resistance and contact temperature for power automotive connector","authors":"Amine Beloufa","doi":"10.1177/09544070241266872","DOIUrl":"https://doi.org/10.1177/09544070241266872","url":null,"abstract":"Power automotive connectors used to connect two electrical systems in an electric vehicle should resist the rising of electric power or electric current. The latter can cause a rise in contact temperature by the Joule effect and can damage a connector improperly designed. The purpose of this work is to study experimentally and numerically the influence of the addition of a second spring on the ability of a power connector to transmit a high current. For this reason, an experimental test has been held on a connector without a second spring to measure contact resistance and contact temperature; then, a finite element model FEM of this connector was developed to compare and validate the numerical results with the experimental results. In addition, another FE model with a second spring was used to minimize contact resistance and contact temperature. Moreover, a theoretical model has shown its effectiveness in contact temperature and contact area calculations; it provides good agreement with experimental and numerical results. Numerical results show that the effect of the addition of a 2nd spring on the decrease of the contact temperature and contact resistance is significant. In addition, the thermo-electrical analysis by finite element shows that the current limit supported by a power connector with an auxiliary spring will equal twice the current supported by a power connector with one spring. FE mechanical analysis shows that the maximum mechanical stress in the connector with an auxiliary spring remains lower than the 2nd spring material yield stress. Finally, experimental and numerical results are in good agreement.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-03DOI: 10.1177/09544070241264600
Lei Cai, Hsin Guan, Qi Hong Xu, Xin Jia, Jun Zhan
Unsignalized intersections are a common scenario in urban areas. Therefore, it is necessary to consider decisions at unsignalized intersections. Left-turn behavior is used as a representative because there are more cases of interactions with other traffic participants under left-turn behavior. First, the paper proposes a way to improve the efficiency and comfort of the host vehicle when the intersection is obscured. Second, a dynamic game theory is proposed based on the potential conflict area of the intersection, considering safety and traffic efficiency. An estimation of the aggressiveness model based on the potential conflict area is proposed. Thirdly, a driving scheme is proposed by adjusting the passing scheme when the game is yielding. Finally, it was simulated for validation at unsignalized intersections by VTD (Virtual Test Drive). Simulation results show that the proposed method can balance comfort and passing efficiency through unsignalized intersections in the presence of occlusion. The average speed of the proposed method through the intersection is higher when interacting with traffic participants.
{"title":"Automatic driving decision-making on left-turn behavior at unsignalized intersections","authors":"Lei Cai, Hsin Guan, Qi Hong Xu, Xin Jia, Jun Zhan","doi":"10.1177/09544070241264600","DOIUrl":"https://doi.org/10.1177/09544070241264600","url":null,"abstract":"Unsignalized intersections are a common scenario in urban areas. Therefore, it is necessary to consider decisions at unsignalized intersections. Left-turn behavior is used as a representative because there are more cases of interactions with other traffic participants under left-turn behavior. First, the paper proposes a way to improve the efficiency and comfort of the host vehicle when the intersection is obscured. Second, a dynamic game theory is proposed based on the potential conflict area of the intersection, considering safety and traffic efficiency. An estimation of the aggressiveness model based on the potential conflict area is proposed. Thirdly, a driving scheme is proposed by adjusting the passing scheme when the game is yielding. Finally, it was simulated for validation at unsignalized intersections by VTD (Virtual Test Drive). Simulation results show that the proposed method can balance comfort and passing efficiency through unsignalized intersections in the presence of occlusion. The average speed of the proposed method through the intersection is higher when interacting with traffic participants.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-03DOI: 10.1177/09544070241265401
Lei Cai, Hsin Guan, Qi Hong Xu, Xin Jia, Jun Zhan
Lane changing is one of the common behaviors in urban and highway scenarios. Therefore, lane-changing behavior is very important in autonomous driving decisions. First, lane change (LC) decisions are divided into waiting to LC, overtaking, LC, and returning to the original lane (RTOL). The LC can be divided into a lane change preparation phase (LCPP), a lane change execution phase (LCEP) 1, and a LCEP 2. The driving intention during the LCPP is further determined by determining the optimal longitudinal acceleration during the LCPP. Second, the conditions under which the host vehicle (HV) chooses to overtake, wait to LC, and choose to LC are proposed, that is, a method for determining the choice of different LC driving options. A condition is proposed for HV to give up overtaking. Third, the practice of determining the interaction process between the host and rear vehicles based on the potential conflict area (PCA) is proposed in LCEP 1. The interaction between the two cars is constructed using a dynamic game method. Finally, VTD (Virtual Test Drive) simulates and verifies the proposed LC decision system.
{"title":"A multi-phase lane change decision-making method for autonomous vehicles","authors":"Lei Cai, Hsin Guan, Qi Hong Xu, Xin Jia, Jun Zhan","doi":"10.1177/09544070241265401","DOIUrl":"https://doi.org/10.1177/09544070241265401","url":null,"abstract":"Lane changing is one of the common behaviors in urban and highway scenarios. Therefore, lane-changing behavior is very important in autonomous driving decisions. First, lane change (LC) decisions are divided into waiting to LC, overtaking, LC, and returning to the original lane (RTOL). The LC can be divided into a lane change preparation phase (LCPP), a lane change execution phase (LCEP) 1, and a LCEP 2. The driving intention during the LCPP is further determined by determining the optimal longitudinal acceleration during the LCPP. Second, the conditions under which the host vehicle (HV) chooses to overtake, wait to LC, and choose to LC are proposed, that is, a method for determining the choice of different LC driving options. A condition is proposed for HV to give up overtaking. Third, the practice of determining the interaction process between the host and rear vehicles based on the potential conflict area (PCA) is proposed in LCEP 1. The interaction between the two cars is constructed using a dynamic game method. Finally, VTD (Virtual Test Drive) simulates and verifies the proposed LC decision system.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Imitation learning struggles to learn an optimal policy from datasets containing both expert and non-expert samples due to its inability to discern the quality differences between these samples. Furthermore, standard online reinforcement learning (RL) methodologies face significant exploration costs and safety risks during environmental interactions. Addressing these challenges, this study develops a lane-changing model for autonomous vehicles using the bootstrapping error accumulation reduction (BEAR) algorithm. The model initially examines the distributional shifts between behavioral and target policies in offline RL. It then incorporates the BEAR algorithm, enhanced with support set constraints, to mitigate this issue. The study subsequently proposes a lane-changing policy learning method based on the BEAR algorithm in offline RL. This method involves designing the state space, action set, and reward function. The reward function is tailored to guide the autonomous vehicle in executing lane changes while balancing safety, ride comfort, and traffic efficiency. In the final stage, the lane-changing policy is learned using a dataset of both expert and non-expert samples. Test results indicate that the lane-changing policy developed through this method shows higher success rates and safety levels compared to policies derived via imitation learning.
{"title":"Lane-changing policy offline reinforcement learning of autonomous vehicles based on BEAR algorithm with support set constraints","authors":"Caixia Huang, Yuxiang Wang, Zhiyong Zhang, Wenming Feng, Dayang Huang","doi":"10.1177/09544070241265752","DOIUrl":"https://doi.org/10.1177/09544070241265752","url":null,"abstract":"Imitation learning struggles to learn an optimal policy from datasets containing both expert and non-expert samples due to its inability to discern the quality differences between these samples. Furthermore, standard online reinforcement learning (RL) methodologies face significant exploration costs and safety risks during environmental interactions. Addressing these challenges, this study develops a lane-changing model for autonomous vehicles using the bootstrapping error accumulation reduction (BEAR) algorithm. The model initially examines the distributional shifts between behavioral and target policies in offline RL. It then incorporates the BEAR algorithm, enhanced with support set constraints, to mitigate this issue. The study subsequently proposes a lane-changing policy learning method based on the BEAR algorithm in offline RL. This method involves designing the state space, action set, and reward function. The reward function is tailored to guide the autonomous vehicle in executing lane changes while balancing safety, ride comfort, and traffic efficiency. In the final stage, the lane-changing policy is learned using a dataset of both expert and non-expert samples. Test results indicate that the lane-changing policy developed through this method shows higher success rates and safety levels compared to policies derived via imitation learning.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.1177/09544070241265763
Hongbin Ren, Yunong Li, Yang Wang, Chih-Keng Chen, Lin Yang, Yuzhuang Zhao
The control performance of model predictive control (MPC) strongly depends on the accuracy of the model description. To better capture and predict the dynamic behaviors of the controlled plant, a non-parametric model which is regressed by the Gaussian Process (GP) is proposed in this paper to evaluate the unknown deviation between the nominal model and the physical system. Firstly, an efficient MPC formulation that integrates a nominal model with GP model which evaluates the unmodeled dynamics is designed for safe and robust maneuver planning. Secondly, the geometric hard constraints for collision avoidance between ego cars and obstacles are softened by using a relaxed barrier function for optimization efficiency. A configuration space convexification algorithm is designed for convexifying the corridor constraints in path pre-selection and re-planned for obstacle avoidance. The control performance of the learning-based MPC is demonstrated and compared with the standard MPC strategy under two typical scenarios. Numerical simulation as well as experiment results indicate that the proposed method could keep the safety, stability, and maneuverability of the ego vehicle during obstacle avoidance.
模型预测控制（MPC）的控制性能在很大程度上取决于模型描述的准确性。为了更好地捕捉和预测受控设备的动态行为，本文提出了一种由高斯过程（GP）回归的非参数模型，用于评估标称模型与物理系统之间的未知偏差。首先，本文设计了一种高效的 MPC 公式，将标称模型与评估未建模动态的 GP 模型整合在一起，以实现安全稳健的机动规划。其次，为了提高优化效率，通过使用松弛的障碍函数来软化避免小车与障碍物碰撞的几何硬约束。设计了一种配置空间凸化算法，用于凸化路径预选中的走廊约束，并重新规划避障。演示了基于学习的 MPC 的控制性能，并在两个典型场景下与标准 MPC 策略进行了比较。数值模拟和实验结果表明，所提出的方法可以在避障过程中保持小我车辆的安全性、稳定性和可操作性。
{"title":"Learning-based model predictive control for safe path planning and control","authors":"Hongbin Ren, Yunong Li, Yang Wang, Chih-Keng Chen, Lin Yang, Yuzhuang Zhao","doi":"10.1177/09544070241265763","DOIUrl":"https://doi.org/10.1177/09544070241265763","url":null,"abstract":"The control performance of model predictive control (MPC) strongly depends on the accuracy of the model description. To better capture and predict the dynamic behaviors of the controlled plant, a non-parametric model which is regressed by the Gaussian Process (GP) is proposed in this paper to evaluate the unknown deviation between the nominal model and the physical system. Firstly, an efficient MPC formulation that integrates a nominal model with GP model which evaluates the unmodeled dynamics is designed for safe and robust maneuver planning. Secondly, the geometric hard constraints for collision avoidance between ego cars and obstacles are softened by using a relaxed barrier function for optimization efficiency. A configuration space convexification algorithm is designed for convexifying the corridor constraints in path pre-selection and re-planned for obstacle avoidance. The control performance of the learning-based MPC is demonstrated and compared with the standard MPC strategy under two typical scenarios. Numerical simulation as well as experiment results indicate that the proposed method could keep the safety, stability, and maneuverability of the ego vehicle during obstacle avoidance.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.1177/09544070241266285
Jialing Yao, Yanan Bai, Yunyi Jia
To enhance the performance of trajectory tracking in high-speed autonomous vehicles, this paper adopts a new technology for controlling the vehicle body to tilt toward the inside of a curve, known as “tilting technology.” It achieves this tilt through an active suspension system that inclines the vehicle body toward the inside of the curve, thereby reducing or offsetting the torque generated by gravity with the torque produced by centrifugal force. This significantly improves the vehicle’s handling stability and anti-rollover capability. Integrating this technology with active steering control, a nonlinear model predictive trajectory tracking controller has been designed. For this integrated controller, the Fiala lateral tire force model is used to establish a nonlinear vehicle model with steering-rolling dynamics, while a double-lane-change and single-lane-change tests are designed as the reference paths. To avoid the tilting angle of the vehicle body being too large to exceed the effective stroke of the suspension, a clipped ideal tilt angle is adopted as the desired tilting angle. Simulation verification is carried out to confirm the validity of the integrated trajectory tracking control. The proposed controller is compared with two other trajectory tracking controllers, the controller that takes zero rolling angle as the control target and the controller without rolling control. The results show that, compared with the latter two, the proposed trajectory tracking controller can ensure well tracking ability, meanwhile effectively improving the handling stability, anti-rollover capability, and occupant lateral ride comfort during trajectory tracking for high-speed unmanned vehicles.
{"title":"Nonlinear model predictive control of vehicle trajectory tracking using tilting technology","authors":"Jialing Yao, Yanan Bai, Yunyi Jia","doi":"10.1177/09544070241266285","DOIUrl":"https://doi.org/10.1177/09544070241266285","url":null,"abstract":"To enhance the performance of trajectory tracking in high-speed autonomous vehicles, this paper adopts a new technology for controlling the vehicle body to tilt toward the inside of a curve, known as “tilting technology.” It achieves this tilt through an active suspension system that inclines the vehicle body toward the inside of the curve, thereby reducing or offsetting the torque generated by gravity with the torque produced by centrifugal force. This significantly improves the vehicle’s handling stability and anti-rollover capability. Integrating this technology with active steering control, a nonlinear model predictive trajectory tracking controller has been designed. For this integrated controller, the Fiala lateral tire force model is used to establish a nonlinear vehicle model with steering-rolling dynamics, while a double-lane-change and single-lane-change tests are designed as the reference paths. To avoid the tilting angle of the vehicle body being too large to exceed the effective stroke of the suspension, a clipped ideal tilt angle is adopted as the desired tilting angle. Simulation verification is carried out to confirm the validity of the integrated trajectory tracking control. The proposed controller is compared with two other trajectory tracking controllers, the controller that takes zero rolling angle as the control target and the controller without rolling control. The results show that, compared with the latter two, the proposed trajectory tracking controller can ensure well tracking ability, meanwhile effectively improving the handling stability, anti-rollover capability, and occupant lateral ride comfort during trajectory tracking for high-speed unmanned vehicles.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.1177/09544070241265773
Bernardo Tormos, Benjamín Pla, Pau Bares, Douglas Pinto
The development of electrified vehicles is a promising step toward energy savings, emissions reduction, environmental protection, and more sustainable economic growth. In the case of hybrid electric vehicles (HEVs), the energy management strategy (EMS) is essential for their efficiency and energy consumption. Typically, EMS employs rule-based strategies calibrated to general driving conditions. So, this paper proposes to calibrate the EMS of an urban hybrid electric bus that covers a particular route by taking advantage of past driving information. The EMS computes the percentage of the vehicle power demand that must be supplied by each of the sources (fuel and battery) and also controls the heating, ventilating and air conditioning (HVAC) system to achieve cabin thermal comfort. The proposed approach is based on employing an optimal solution by dynamic programing in a previous loop covered by the bus in the considered route. Then, the cost-to-go matrix is stored and used in the following trips by applying the one-step look-ahead rollout, taking profit from the similarities of the loops in the route. To compare and evaluate the performance of the proposed algorithm, a benchmark was carried out by employing the widespread equivalent consumption minimization strategy (ECMS) approach, combined with rule-based strategies in the HVAC control system. Finally, the pareto front presents the trade-off between cabin temperature control performance and total fuel consumption, allowing to compare and evaluate the different EMS calibrations.
{"title":"A multi-objective energy management optimization for a hybrid electric bus covering an urban route","authors":"Bernardo Tormos, Benjamín Pla, Pau Bares, Douglas Pinto","doi":"10.1177/09544070241265773","DOIUrl":"https://doi.org/10.1177/09544070241265773","url":null,"abstract":"The development of electrified vehicles is a promising step toward energy savings, emissions reduction, environmental protection, and more sustainable economic growth. In the case of hybrid electric vehicles (HEVs), the energy management strategy (EMS) is essential for their efficiency and energy consumption. Typically, EMS employs rule-based strategies calibrated to general driving conditions. So, this paper proposes to calibrate the EMS of an urban hybrid electric bus that covers a particular route by taking advantage of past driving information. The EMS computes the percentage of the vehicle power demand that must be supplied by each of the sources (fuel and battery) and also controls the heating, ventilating and air conditioning (HVAC) system to achieve cabin thermal comfort. The proposed approach is based on employing an optimal solution by dynamic programing in a previous loop covered by the bus in the considered route. Then, the cost-to-go matrix is stored and used in the following trips by applying the one-step look-ahead rollout, taking profit from the similarities of the loops in the route. To compare and evaluate the performance of the proposed algorithm, a benchmark was carried out by employing the widespread equivalent consumption minimization strategy (ECMS) approach, combined with rule-based strategies in the HVAC control system. Finally, the pareto front presents the trade-off between cabin temperature control performance and total fuel consumption, allowing to compare and evaluate the different EMS calibrations.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.1177/09544070241266281
Krisztián Enisz, István Szalay, Ernő Horváth
In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.
{"title":"Localization robustness improvement for an autonomous race car using multiple extended Kalman filters","authors":"Krisztián Enisz, István Szalay, Ernő Horváth","doi":"10.1177/09544070241266281","DOIUrl":"https://doi.org/10.1177/09544070241266281","url":null,"abstract":"In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, automatic guided vehicles (AGV) are extensively utilized for transportation and inspection tasks in workshops. The A* and artificial potential field (APF) are classic algorithms employed for path planning of AGVs. However, these algorithms still fail to meet the actual production needs and cannot avoid stuttering while encountering obstacles, leading to excessive energy consumption and unnecessary pause. In the paper, an improved A* algorithm is proposed to reduce route length and improving efficiency. On this basis, an integrated fusion strategy consisting of improved APF and nonlinear model predictive control (NMPC) is designed for collision avoidance and path tracking control. The proposed algorithm is tested both on simulation and a laser-guided real automatic guided vehicle experimental platform. Experimental results prove that the proposed algorithm has a great tracking performance under complex workplace.
{"title":"MPC-based motion control of AGV with improved A* and artificial potential field","authors":"Shaosong Li, Qingbin Zhou, Junchen Jiang, Xiaohui Lu, Zhixin Yu","doi":"10.1177/09544070241264360","DOIUrl":"https://doi.org/10.1177/09544070241264360","url":null,"abstract":"Nowadays, automatic guided vehicles (AGV) are extensively utilized for transportation and inspection tasks in workshops. The A* and artificial potential field (APF) are classic algorithms employed for path planning of AGVs. However, these algorithms still fail to meet the actual production needs and cannot avoid stuttering while encountering obstacles, leading to excessive energy consumption and unnecessary pause. In the paper, an improved A* algorithm is proposed to reduce route length and improving efficiency. On this basis, an integrated fusion strategy consisting of improved APF and nonlinear model predictive control (NMPC) is designed for collision avoidance and path tracking control. The proposed algorithm is tested both on simulation and a laser-guided real automatic guided vehicle experimental platform. Experimental results prove that the proposed algorithm has a great tracking performance under complex workplace.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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